diff --git a/.github/workflows/format_check.yml b/.github/workflows/format_check.yml
index 8e14535f..e90e24a7 100644
--- a/.github/workflows/format_check.yml
+++ b/.github/workflows/format_check.yml
@@ -20,8 +20,7 @@ jobs:
           using Pkg
           Pkg.add(PackageSpec(name="JuliaFormatter", version="2"))
           using JuliaFormatter
-          format("src", verbose=true)
-          format("test", verbose=true)
+          format("."; verbose = true)
           out = String(read(Cmd(`git diff`)))
           if isempty(out)
               exit(0)
diff --git a/benchmark/Manifest.toml b/benchmark/Manifest.toml
index 9efd0281..c3390186 100644
--- a/benchmark/Manifest.toml
+++ b/benchmark/Manifest.toml
@@ -1,335 +1,394 @@
 # This file is machine-generated - editing it directly is not advised
 
-[[ArgTools]]
-uuid = "0dad84c5-d112-42e6-8d28-ef12dabb789f"
-
 [[Artifacts]]
 uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
+version = "1.11.0"
 
 [[Base64]]
 uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
+version = "1.11.0"
 
 [[BenchmarkTools]]
-deps = ["JSON", "Logging", "Printf", "Profile", "Statistics", "UUIDs"]
-git-tree-sha1 = "4c10eee4af024676200bc7752e536f858c6b8f93"
+deps = ["Compat", "JSON", "Logging", "Printf", "Profile", "Statistics", "UUIDs"]
+git-tree-sha1 = "7fecfb1123b8d0232218e2da0c213004ff15358d"
 uuid = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-version = "1.3.1"
+version = "1.6.3"
 
 [[Bzip2_jll]]
-deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "19a35467a82e236ff51bc17a3a44b69ef35185a2"
+deps = ["Artifacts", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "1b96ea4a01afe0ea4090c5c8039690672dd13f2e"
 uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0"
-version = "1.0.8+0"
-
-[[Calculus]]
-deps = ["LinearAlgebra"]
-git-tree-sha1 = "f641eb0a4f00c343bbc32346e1217b86f3ce9dad"
-uuid = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
-version = "0.5.1"
-
-[[ChainRulesCore]]
-deps = ["Compat", "LinearAlgebra", "SparseArrays"]
-git-tree-sha1 = "2dd813e5f2f7eec2d1268c57cf2373d3ee91fcea"
-uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "1.15.1"
-
-[[ChangesOfVariables]]
-deps = ["ChainRulesCore", "LinearAlgebra", "Test"]
-git-tree-sha1 = "1e315e3f4b0b7ce40feded39c73049692126cf53"
-uuid = "9e997f8a-9a97-42d5-a9f1-ce6bfc15e2c0"
-version = "0.1.3"
+version = "1.0.9+0"
 
 [[CodecBzip2]]
-deps = ["Bzip2_jll", "Libdl", "TranscodingStreams"]
-git-tree-sha1 = "2e62a725210ce3c3c2e1a3080190e7ca491f18d7"
+deps = ["Bzip2_jll", "TranscodingStreams"]
+git-tree-sha1 = "84990fa864b7f2b4901901ca12736e45ee79068c"
 uuid = "523fee87-0ab8-5b00-afb7-3ecf72e48cfd"
-version = "0.7.2"
+version = "0.8.5"
 
 [[CodecZlib]]
 deps = ["TranscodingStreams", "Zlib_jll"]
-git-tree-sha1 = "ded953804d019afa9a3f98981d99b33e3db7b6da"
+git-tree-sha1 = "962834c22b66e32aa10f7611c08c8ca4e20749a9"
 uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
-version = "0.7.0"
+version = "0.7.8"
 
 [[CommonSubexpressions]]
-deps = ["MacroTools", "Test"]
-git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7"
+deps = ["MacroTools"]
+git-tree-sha1 = "cda2cfaebb4be89c9084adaca7dd7333369715c5"
 uuid = "bbf7d656-a473-5ed7-a52c-81e309532950"
-version = "0.3.0"
+version = "0.3.1"
 
 [[Compat]]
-deps = ["Dates", "LinearAlgebra", "UUIDs"]
-git-tree-sha1 = "924cdca592bc16f14d2f7006754a621735280b74"
+deps = ["TOML", "UUIDs"]
+git-tree-sha1 = "9d8a54ce4b17aa5bdce0ea5c34bc5e7c340d16ad"
 uuid = "34da2185-b29b-5c13-b0c7-acf172513d20"
-version = "4.1.0"
+version = "4.18.1"
+weakdeps = ["Dates", "LinearAlgebra"]
+
+    [Compat.extensions]
+    CompatLinearAlgebraExt = "LinearAlgebra"
 
 [[CompilerSupportLibraries_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae"
-
-[[DataStructures]]
-deps = ["Compat", "InteractiveUtils", "OrderedCollections"]
-git-tree-sha1 = "d1fff3a548102f48987a52a2e0d114fa97d730f0"
-uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
-version = "0.18.13"
+version = "1.3.0+1"
 
 [[Dates]]
 deps = ["Printf"]
 uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"
+version = "1.11.0"
 
 [[DiffResults]]
-deps = ["StaticArrays"]
-git-tree-sha1 = "c18e98cba888c6c25d1c3b048e4b3380ca956805"
+deps = ["StaticArraysCore"]
+git-tree-sha1 = "782dd5f4561f5d267313f23853baaaa4c52ea621"
 uuid = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
-version = "1.0.3"
+version = "1.1.0"
 
 [[DiffRules]]
 deps = ["IrrationalConstants", "LogExpFunctions", "NaNMath", "Random", "SpecialFunctions"]
-git-tree-sha1 = "28d605d9a0ac17118fe2c5e9ce0fbb76c3ceb120"
+git-tree-sha1 = "23163d55f885173722d1e4cf0f6110cdbaf7e272"
 uuid = "b552c78f-8df3-52c6-915a-8e097449b14b"
-version = "1.11.0"
+version = "1.15.1"
 
 [[DocStringExtensions]]
-deps = ["LibGit2"]
-git-tree-sha1 = "b19534d1895d702889b219c382a6e18010797f0b"
+git-tree-sha1 = "7442a5dfe1ebb773c29cc2962a8980f47221d76c"
 uuid = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
-version = "0.8.6"
+version = "0.9.5"
 
-[[Downloads]]
-deps = ["ArgTools", "LibCURL", "NetworkOptions"]
-uuid = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
+[[ExprTools]]
+git-tree-sha1 = "27415f162e6028e81c72b82ef756bf321213b6ec"
+uuid = "e2ba6199-217a-4e67-a87a-7c52f15ade04"
+version = "0.1.10"
 
 [[ForwardDiff]]
-deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "LinearAlgebra", "LogExpFunctions", "NaNMath", "Preferences", "Printf", "Random", "SpecialFunctions", "StaticArrays"]
-git-tree-sha1 = "2f18915445b248731ec5db4e4a17e451020bf21e"
+deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "LinearAlgebra", "LogExpFunctions", "NaNMath", "Preferences", "Printf", "Random", "SpecialFunctions"]
+git-tree-sha1 = "eef4c86803f47dcb61e9b8790ecaa96956fdd8ae"
 uuid = "f6369f11-7733-5829-9624-2563aa707210"
-version = "0.10.30"
+version = "1.3.2"
+
+    [ForwardDiff.extensions]
+    ForwardDiffStaticArraysExt = "StaticArrays"
+
+    [ForwardDiff.weakdeps]
+    StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
+
+[[HiGHS]]
+deps = ["HiGHS_jll", "LinearAlgebra", "MathOptIIS", "MathOptInterface", "OpenBLAS32_jll", "PrecompileTools", "SparseArrays"]
+git-tree-sha1 = "900d431a604b096953437855a3d5fd03a18c3a6c"
+uuid = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
+version = "1.21.1"
+
+[[HiGHS_jll]]
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Zlib_jll", "libblastrampoline_jll"]
+git-tree-sha1 = "621d773f277b9eadac7e049eaa6418af65c7b9d7"
+uuid = "8fd58aa0-07eb-5a78-9b36-339c94fd15ea"
+version = "1.13.1+0"
 
 [[InteractiveUtils]]
 deps = ["Markdown"]
 uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
-
-[[InverseFunctions]]
-deps = ["Test"]
-git-tree-sha1 = "b3364212fb5d870f724876ffcd34dd8ec6d98918"
-uuid = "3587e190-3f89-42d0-90ee-14403ec27112"
-version = "0.1.7"
+version = "1.11.0"
 
 [[IrrationalConstants]]
-git-tree-sha1 = "7fd44fd4ff43fc60815f8e764c0f352b83c49151"
+git-tree-sha1 = "b2d91fe939cae05960e760110b328288867b5758"
 uuid = "92d709cd-6900-40b7-9082-c6be49f344b6"
-version = "0.1.1"
+version = "0.2.6"
 
 [[JLLWrappers]]
-deps = ["Preferences"]
-git-tree-sha1 = "abc9885a7ca2052a736a600f7fa66209f96506e1"
+deps = ["Artifacts", "Preferences"]
+git-tree-sha1 = "0533e564aae234aff59ab625543145446d8b6ec2"
 uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
-version = "1.4.1"
+version = "1.7.1"
 
 [[JSON]]
-deps = ["Dates", "Mmap", "Parsers", "Unicode"]
-git-tree-sha1 = "3c837543ddb02250ef42f4738347454f95079d4e"
+deps = ["Dates", "Logging", "Parsers", "PrecompileTools", "StructUtils", "UUIDs", "Unicode"]
+git-tree-sha1 = "b3ad4a0255688dcb895a52fafbaae3023b588a90"
 uuid = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
-version = "0.21.3"
+version = "1.4.0"
+
+    [JSON.extensions]
+    JSONArrowExt = ["ArrowTypes"]
+
+    [JSON.weakdeps]
+    ArrowTypes = "31f734f8-188a-4ce0-8406-c8a06bd891cd"
 
 [[JuMP]]
-deps = ["Calculus", "DataStructures", "ForwardDiff", "LinearAlgebra", "MathOptInterface", "MutableArithmetics", "NaNMath", "OrderedCollections", "Printf", "SparseArrays", "SpecialFunctions"]
-git-tree-sha1 = "936e7ebf6c84f0c0202b83bb22461f4ebc5c9969"
+deps = ["LinearAlgebra", "MacroTools", "MathOptInterface", "MutableArithmetics", "OrderedCollections", "PrecompileTools", "Printf", "SparseArrays"]
+git-tree-sha1 = "8e4088727b5a130c12b1fedbc316306b6bbf2b9d"
 uuid = "4076af6c-e467-56ae-b986-b466b2749572"
-version = "1.0.0"
+version = "1.29.4"
 
-[[LibCURL]]
-deps = ["LibCURL_jll", "MozillaCACerts_jll"]
-uuid = "b27032c2-a3e7-50c8-80cd-2d36dbcbfd21"
+    [JuMP.extensions]
+    JuMPDimensionalDataExt = "DimensionalData"
 
-[[LibCURL_jll]]
-deps = ["Artifacts", "LibSSH2_jll", "Libdl", "MbedTLS_jll", "Zlib_jll", "nghttp2_jll"]
-uuid = "deac9b47-8bc7-5906-a0fe-35ac56dc84c0"
+    [JuMP.weakdeps]
+    DimensionalData = "0703355e-b756-11e9-17c0-8b28908087d0"
 
-[[LibGit2]]
-deps = ["Base64", "NetworkOptions", "Printf", "SHA"]
-uuid = "76f85450-5226-5b5a-8eaa-529ad045b433"
-
-[[LibSSH2_jll]]
-deps = ["Artifacts", "Libdl", "MbedTLS_jll"]
-uuid = "29816b5a-b9ab-546f-933c-edad1886dfa8"
+[[JuliaSyntaxHighlighting]]
+deps = ["StyledStrings"]
+uuid = "ac6e5ff7-fb65-4e79-a425-ec3bc9c03011"
+version = "1.12.0"
 
 [[Libdl]]
 uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
+version = "1.11.0"
 
 [[LinearAlgebra]]
-deps = ["Libdl"]
+deps = ["Libdl", "OpenBLAS_jll", "libblastrampoline_jll"]
 uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+version = "1.12.0"
 
 [[LogExpFunctions]]
-deps = ["ChainRulesCore", "ChangesOfVariables", "DocStringExtensions", "InverseFunctions", "IrrationalConstants", "LinearAlgebra"]
-git-tree-sha1 = "09e4b894ce6a976c354a69041a04748180d43637"
+deps = ["DocStringExtensions", "IrrationalConstants", "LinearAlgebra"]
+git-tree-sha1 = "13ca9e2586b89836fd20cccf56e57e2b9ae7f38f"
 uuid = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
-version = "0.3.15"
+version = "0.3.29"
+
+    [LogExpFunctions.extensions]
+    LogExpFunctionsChainRulesCoreExt = "ChainRulesCore"
+    LogExpFunctionsChangesOfVariablesExt = "ChangesOfVariables"
+    LogExpFunctionsInverseFunctionsExt = "InverseFunctions"
+
+    [LogExpFunctions.weakdeps]
+    ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
+    ChangesOfVariables = "9e997f8a-9a97-42d5-a9f1-ce6bfc15e2c0"
+    InverseFunctions = "3587e190-3f89-42d0-90ee-14403ec27112"
 
 [[Logging]]
 uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
+version = "1.11.0"
 
 [[MacroTools]]
-deps = ["Markdown", "Random"]
-git-tree-sha1 = "3d3e902b31198a27340d0bf00d6ac452866021cf"
+git-tree-sha1 = "1e0228a030642014fe5cfe68c2c0a818f9e3f522"
 uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
-version = "0.5.9"
+version = "0.5.16"
 
 [[Markdown]]
-deps = ["Base64"]
+deps = ["Base64", "JuliaSyntaxHighlighting", "StyledStrings"]
 uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
+version = "1.11.0"
+
+[[MathOptIIS]]
+deps = ["MathOptInterface"]
+git-tree-sha1 = "31d4a6353ea00603104f11384aa44dd8b7162b28"
+uuid = "8c4f8055-bd93-4160-a86b-a0c04941dbff"
+version = "0.1.1"
 
 [[MathOptInterface]]
-deps = ["BenchmarkTools", "CodecBzip2", "CodecZlib", "DataStructures", "ForwardDiff", "JSON", "LinearAlgebra", "MutableArithmetics", "NaNMath", "OrderedCollections", "Printf", "SparseArrays", "SpecialFunctions", "Test", "Unicode"]
-git-tree-sha1 = "10d26d62dab815306bbd2c46eb52460e98f01e46"
+deps = ["BenchmarkTools", "CodecBzip2", "CodecZlib", "ForwardDiff", "JSON", "LinearAlgebra", "MutableArithmetics", "NaNMath", "OrderedCollections", "PrecompileTools", "Printf", "SparseArrays", "SpecialFunctions", "Test"]
+git-tree-sha1 = "7fb98657926ccb4de8f9bb96cda453700ca39a8b"
 uuid = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
-version = "1.6.0"
-
-[[MbedTLS_jll]]
-deps = ["Artifacts", "Libdl"]
-uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"
-
-[[Mmap]]
-uuid = "a63ad114-7e13-5084-954f-fe012c677804"
-
-[[MozillaCACerts_jll]]
-uuid = "14a3606d-f60d-562e-9121-12d972cd8159"
+version = "1.49.0"
 
 [[MutableArithmetics]]
 deps = ["LinearAlgebra", "SparseArrays", "Test"]
-git-tree-sha1 = "4e675d6e9ec02061800d6cfb695812becbd03cdf"
+git-tree-sha1 = "22df8573f8e7c593ac205455ca088989d0a2c7a0"
 uuid = "d8a4904e-b15c-11e9-3269-09a3773c0cb0"
-version = "1.0.4"
+version = "1.6.7"
 
 [[NaNMath]]
-git-tree-sha1 = "737a5957f387b17e74d4ad2f440eb330b39a62c5"
+deps = ["OpenLibm_jll"]
+git-tree-sha1 = "9b8215b1ee9e78a293f99797cd31375471b2bcae"
 uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
-version = "1.0.0"
+version = "1.1.3"
+
+[[OpenBLAS32_jll]]
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "46cce8b42186882811da4ce1f4c7208b02deb716"
+uuid = "656ef2d0-ae68-5445-9ca0-591084a874a2"
+version = "0.3.30+0"
 
-[[NetworkOptions]]
-uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
+[[OpenBLAS_jll]]
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "Libdl"]
+uuid = "4536629a-c528-5b80-bd46-f80d51c5b363"
+version = "0.3.29+0"
 
 [[OpenLibm_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "05823500-19ac-5b8b-9628-191a04bc5112"
+version = "0.8.7+0"
 
 [[OpenSpecFun_jll]]
-deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "13652491f6856acfd2db29360e1bbcd4565d04f1"
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl"]
+git-tree-sha1 = "1346c9208249809840c91b26703912dff463d335"
 uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
-version = "0.5.5+0"
+version = "0.5.6+0"
 
 [[OrderedCollections]]
-git-tree-sha1 = "85f8e6578bf1f9ee0d11e7bb1b1456435479d47c"
+git-tree-sha1 = "05868e21324cede2207c6f0f466b4bfef6d5e7ee"
 uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-version = "1.4.1"
+version = "1.8.1"
+
+[[ParameterJuMP]]
+deps = ["JuMP", "MathOptInterface", "MutableArithmetics", "SparseArrays"]
+git-tree-sha1 = "a7ea1d5263f9a3aa0670fbcc58c2cca275baa3fc"
+uuid = "774612a8-9878-5177-865a-ca53ae2495f9"
+version = "0.4.1"
 
 [[ParametricOptInterface]]
 deps = ["MathOptInterface"]
-git-tree-sha1 = "4f0dfcc0c4f42c1baf4774ba9c0a397ae309c625"
+path = ".."
 uuid = "0ce4ce61-57bf-432b-a095-efac525d185e"
-version = "0.4.1"
+version = "0.14.2"
 
 [[Parsers]]
-deps = ["Dates"]
-git-tree-sha1 = "0044b23da09b5608b4ecacb4e5e6c6332f833a7e"
+deps = ["Dates", "PrecompileTools", "UUIDs"]
+git-tree-sha1 = "7d2f8f21da5db6a806faf7b9b292296da42b2810"
 uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
-version = "2.3.2"
+version = "2.8.3"
 
-[[Pkg]]
-deps = ["Artifacts", "Dates", "Downloads", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "Serialization", "TOML", "Tar", "UUIDs", "p7zip_jll"]
-uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+[[PrecompileTools]]
+deps = ["Preferences"]
+git-tree-sha1 = "07a921781cab75691315adc645096ed5e370cb77"
+uuid = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
+version = "1.3.3"
 
 [[Preferences]]
 deps = ["TOML"]
-git-tree-sha1 = "47e5f437cc0e7ef2ce8406ce1e7e24d44915f88d"
+git-tree-sha1 = "522f093a29b31a93e34eaea17ba055d850edea28"
 uuid = "21216c6a-2e73-6563-6e65-726566657250"
-version = "1.3.0"
+version = "1.5.1"
 
 [[Printf]]
 deps = ["Unicode"]
 uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+version = "1.11.0"
 
 [[Profile]]
-deps = ["Printf"]
+deps = ["StyledStrings"]
 uuid = "9abbd945-dff8-562f-b5e8-e1ebf5ef1b79"
-
-[[REPL]]
-deps = ["InteractiveUtils", "Markdown", "Sockets", "Unicode"]
-uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
+version = "1.11.0"
 
 [[Random]]
-deps = ["Serialization"]
+deps = ["SHA"]
 uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+version = "1.11.0"
 
 [[SHA]]
 uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
+version = "0.7.0"
 
 [[Serialization]]
 uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
-
-[[Sockets]]
-uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
+version = "1.11.0"
 
 [[SparseArrays]]
-deps = ["LinearAlgebra", "Random"]
+deps = ["Libdl", "LinearAlgebra", "Random", "Serialization", "SuiteSparse_jll"]
 uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+version = "1.12.0"
 
 [[SpecialFunctions]]
-deps = ["ChainRulesCore", "IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
-git-tree-sha1 = "d75bda01f8c31ebb72df80a46c88b25d1c79c56d"
+deps = ["IrrationalConstants", "LogExpFunctions", "OpenLibm_jll", "OpenSpecFun_jll"]
+git-tree-sha1 = "5acc6a41b3082920f79ca3c759acbcecf18a8d78"
 uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
-version = "2.1.7"
+version = "2.7.1"
 
-[[StaticArrays]]
-deps = ["LinearAlgebra", "Random", "StaticArraysCore", "Statistics"]
-git-tree-sha1 = "e972716025466461a3dc1588d9168334b71aafff"
-uuid = "90137ffa-7385-5640-81b9-e52037218182"
-version = "1.5.1"
+    [SpecialFunctions.extensions]
+    SpecialFunctionsChainRulesCoreExt = "ChainRulesCore"
+
+    [SpecialFunctions.weakdeps]
+    ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 
 [[StaticArraysCore]]
-git-tree-sha1 = "66fe9eb253f910fe8cf161953880cfdaef01cdf0"
+git-tree-sha1 = "6ab403037779dae8c514bad259f32a447262455a"
 uuid = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
-version = "1.0.1"
+version = "1.4.4"
 
 [[Statistics]]
-deps = ["LinearAlgebra", "SparseArrays"]
+deps = ["LinearAlgebra"]
+git-tree-sha1 = "ae3bb1eb3bba077cd276bc5cfc337cc65c3075c0"
 uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+version = "1.11.1"
+weakdeps = ["SparseArrays"]
+
+    [Statistics.extensions]
+    SparseArraysExt = ["SparseArrays"]
+
+[[StructUtils]]
+deps = ["Dates", "UUIDs"]
+git-tree-sha1 = "28145feabf717c5d65c1d5e09747ee7b1ff3ed13"
+uuid = "ec057cc2-7a8d-4b58-b3b3-92acb9f63b42"
+version = "2.6.3"
+
+    [StructUtils.extensions]
+    StructUtilsMeasurementsExt = ["Measurements"]
+    StructUtilsTablesExt = ["Tables"]
+
+    [StructUtils.weakdeps]
+    Measurements = "eff96d63-e80a-5855-80a2-b1b0885c5ab7"
+    Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
+
+[[StyledStrings]]
+uuid = "f489334b-da3d-4c2e-b8f0-e476e12c162b"
+version = "1.11.0"
+
+[[SuiteSparse_jll]]
+deps = ["Artifacts", "Libdl", "libblastrampoline_jll"]
+uuid = "bea87d4a-7f5b-5778-9afe-8cc45184846c"
+version = "7.8.3+2"
 
 [[TOML]]
 deps = ["Dates"]
 uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
-
-[[Tar]]
-deps = ["ArgTools", "SHA"]
-uuid = "a4e569a6-e804-4fa4-b0f3-eef7a1d5b13e"
+version = "1.0.3"
 
 [[Test]]
 deps = ["InteractiveUtils", "Logging", "Random", "Serialization"]
 uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+version = "1.11.0"
+
+[[TimerOutputs]]
+deps = ["ExprTools", "Printf"]
+git-tree-sha1 = "3748bd928e68c7c346b52125cf41fff0de6937d0"
+uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
+version = "0.5.29"
+
+    [TimerOutputs.extensions]
+    FlameGraphsExt = "FlameGraphs"
+
+    [TimerOutputs.weakdeps]
+    FlameGraphs = "08572546-2f56-4bcf-ba4e-bab62c3a3f89"
 
 [[TranscodingStreams]]
-deps = ["Random", "Test"]
-git-tree-sha1 = "216b95ea110b5972db65aa90f88d8d89dcb8851c"
+git-tree-sha1 = "0c45878dcfdcfa8480052b6ab162cdd138781742"
 uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
-version = "0.9.6"
+version = "0.11.3"
 
 [[UUIDs]]
 deps = ["Random", "SHA"]
 uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+version = "1.11.0"
 
 [[Unicode]]
 uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
+version = "1.11.0"
 
 [[Zlib_jll]]
 deps = ["Libdl"]
 uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
+version = "1.3.1+2"
 
-[[nghttp2_jll]]
-deps = ["Artifacts", "Libdl"]
-uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
-
-[[p7zip_jll]]
+[[libblastrampoline_jll]]
 deps = ["Artifacts", "Libdl"]
-uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"
+uuid = "8e850b90-86db-534c-a0d3-1478176c7d93"
+version = "5.15.0+0"
diff --git a/benchmark/Project.toml b/benchmark/Project.toml
index 4e7a00ee..124b3824 100644
--- a/benchmark/Project.toml
+++ b/benchmark/Project.toml
@@ -1,5 +1,9 @@
 [deps]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
+HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
+ParameterJuMP = "774612a8-9878-5177-865a-ca53ae2495f9"
 ParametricOptInterface = "0ce4ce61-57bf-432b-a095-efac525d185e"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
diff --git a/benchmark/run_benchmarks.jl b/benchmark/run_benchmarks.jl
index bdc66680..f71a8a11 100644
--- a/benchmark/run_benchmarks.jl
+++ b/benchmark/run_benchmarks.jl
@@ -3,36 +3,35 @@
 # Use of this source code is governed by an MIT-style license that can be found
 # in the LICENSE.md file or at https://opensource.org/licenses/MIT.
 
-using MathOptInterface
-using ParametricOptInterface
 using BenchmarkTools
-const MOI = MathOptInterface
-const POI = ParametricOptInterface
+
+import MathOptInterface as MOI
+import ParametricOptInterface as POI
 import Pkg
 
 function moi_add_variables(N::Int)
     model = MOI.Utilities.Model{Float64}()
     MOI.add_variables(model, N)
-    return nothing
+    return
 end
 
 function poi_add_variables(N::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     MOI.add_variables(model, N)
-    return nothing
+    return
 end
 
 function poi_add_parameters(N::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     MOI.add_constrained_variable.(model, MOI.Parameter.(ones(N)))
-    return nothing
+    return
 end
 
 function poi_add_parameters_and_variables(N::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     MOI.add_variables(model, N / 2)
     MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
-    return nothing
+    return
 end
 
 function poi_add_parameters_and_variables_alternating(N::Int)
@@ -41,7 +40,7 @@ function poi_add_parameters_and_variables_alternating(N::Int)
         MOI.add_variable(model)
         MOI.add_constrained_variable(model, MOI.Parameter(1.0))
     end
-    return nothing
+    return
 end
 
 function moi_add_saf_ctr(N::Int, M::Int)
@@ -54,7 +53,7 @@ function moi_add_saf_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_ctr(N::Int, M::Int)
@@ -67,7 +66,7 @@ function poi_add_saf_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_ctr(N::Int, M::Int)
@@ -86,7 +85,7 @@ function poi_add_saf_variables_and_parameters_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_ctr_parameter_update(
@@ -110,7 +109,7 @@ function poi_add_saf_variables_and_parameters_ctr_parameter_update(
     end
     MOI.set.(model, POI.ParameterValue(), y, 0.5)
     POI.update_parameters!(model)
-    return nothing
+    return
 end
 
 function moi_add_sqf_variables_ctr(N::Int, M::Int)
@@ -127,7 +126,7 @@ function moi_add_sqf_variables_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_ctr(N::Int, M::Int)
@@ -144,7 +143,7 @@ function poi_add_sqf_variables_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_ctr(N::Int, M::Int)
@@ -164,7 +163,7 @@ function poi_add_sqf_variables_parameters_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
@@ -186,7 +185,7 @@ function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
     end
     MOI.set.(model, POI.ParameterValue(), y, 0.5)
     POI.update_parameters!(model)
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_ctr(N::Int, M::Int)
@@ -206,7 +205,7 @@ function poi_add_sqf_parameters_parameters_ctr(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
@@ -228,7 +227,7 @@ function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
     end
     MOI.set.(model, POI.ParameterValue(), y, 0.5)
     POI.update_parameters!(model)
-    return nothing
+    return
 end
 
 function moi_add_saf_obj(N::Int, M::Int)
@@ -241,7 +240,7 @@ function moi_add_saf_obj(N::Int, M::Int)
             MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(1.0, x), 0.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_obj(N::Int, M::Int)
@@ -254,7 +253,7 @@ function poi_add_saf_obj(N::Int, M::Int)
             MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.(1.0, x), 0.0),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_obj(N::Int, M::Int)
@@ -273,7 +272,7 @@ function poi_add_saf_variables_and_parameters_obj(N::Int, M::Int)
             ),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_obj_parameter_update(
@@ -299,7 +298,7 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
         MOI.set.(model, POI.ParameterValue(), y, 0.5)
         POI.update_parameters!(model)
     end
-    return nothing
+    return
 end
 
 function moi_add_sqf_variables_obj(N::Int, M::Int)
@@ -316,7 +315,7 @@ function moi_add_sqf_variables_obj(N::Int, M::Int)
             ),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_obj(N::Int, M::Int)
@@ -333,7 +332,7 @@ function poi_add_sqf_variables_obj(N::Int, M::Int)
             ),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_obj(N::Int, M::Int)
@@ -353,7 +352,7 @@ function poi_add_sqf_variables_parameters_obj(N::Int, M::Int)
             ),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
@@ -377,7 +376,7 @@ function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
         MOI.set.(model, POI.ParameterValue(), y, 0.5)
         POI.update_parameters!(model)
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_obj(N::Int, M::Int)
@@ -397,7 +396,7 @@ function poi_add_sqf_parameters_parameters_obj(N::Int, M::Int)
             ),
         )
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
@@ -421,7 +420,7 @@ function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
         MOI.set.(model, POI.ParameterValue(), y, 0.5)
         POI.update_parameters!(model)
     end
-    return nothing
+    return
 end
 
 function run_benchmarks(N::Int, M::Int)
@@ -519,7 +518,7 @@ function run_benchmarks(N::Int, M::Int)
         "Update parameters in SQF objective with product of parameters on a POI.Optimizer.",
     )
     @btime poi_add_sqf_parameters_parameters_obj_parameter_update($N, $M)
-    return nothing
+    return
 end
 
 N = 10_000
diff --git a/benchmark/run_benchmarks_jump.jl b/benchmark/run_benchmarks_jump.jl
index 877b2707..6feb9d37 100644
--- a/benchmark/run_benchmarks_jump.jl
+++ b/benchmark/run_benchmarks_jump.jl
@@ -3,11 +3,10 @@
 # Use of this source code is governed by an MIT-style license that can be found
 # in the LICENSE.md file or at https://opensource.org/licenses/MIT.
 
-using ParametricOptInterface
 using BenchmarkTools
 using JuMP
-using LinearAlgebra
-const POI = ParametricOptInterface
+
+import ParametricOptInterface as POI
 import Pkg
 
 function moi_add_variables(N::Int)
@@ -18,7 +17,7 @@ function moi_add_variables(N::Int)
         ),
     )
     @variable(model, x[i=1:N])
-    return nothing
+    return
 end
 
 function poi_add_variables(N::Int)
@@ -31,7 +30,7 @@ function poi_add_variables(N::Int)
         ),
     )
     @variable(model, x[i=1:N])
-    return nothing
+    return
 end
 
 function poi_add_parameters(N::Int)
@@ -43,8 +42,8 @@ function poi_add_parameters(N::Int)
             ),
         ),
     )
-    @variable(model, x[i=1:N] in MOI.Parameter(1.0))
-    return nothing
+    @variable(model, x[i=1:N] in Parameter(1))
+    return
 end
 
 function poi_add_parameters_and_variables(N::Int)
@@ -56,8 +55,8 @@ function poi_add_parameters_and_variables(N::Int)
             ),
         ),
     )
-    @variable(model, x[i=1:N] in MOI.Parameter(1.0))
-    return nothing
+    @variable(model, x[i=1:N] in Parameter(1))
+    return
 end
 
 function poi_add_parameters_and_variables_alternating(N::Int)
@@ -71,9 +70,9 @@ function poi_add_parameters_and_variables_alternating(N::Int)
     )
     for i in 1:Int(N/2)
         @variable(model)
-        @variable(model, set = MOI.Parameter(1.0))
+        @variable(model, set = Parameter(1))
     end
-    return nothing
+    return
 end
 
 function moi_add_saf_ctr(N::Int, M::Int)
@@ -85,7 +84,7 @@ function moi_add_saf_ctr(N::Int, M::Int)
     )
     @variable(model, x[i=1:N])
     @constraint(model, cons[i=1:M], sum(x) >= 1)
-    return nothing
+    return
 end
 
 function poi_add_saf_ctr(N::Int, M::Int)
@@ -99,7 +98,7 @@ function poi_add_saf_ctr(N::Int, M::Int)
     )
     @variable(model, x[i=1:N])
     @constraint(model, cons[i=1:M], sum(x) >= 1)
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_ctr(N::Int, M::Int)
@@ -112,9 +111,9 @@ function poi_add_saf_variables_and_parameters_ctr(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(0))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(0))
     @constraint(model, con[i=1:M], sum(x) + sum(p) >= 1)
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_ctr_parameter_update(
@@ -130,11 +129,11 @@ function poi_add_saf_variables_and_parameters_ctr_parameter_update(
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(0))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(0))
     @constraint(model, con[i=1:M], sum(x) + sum(p) >= 1)
     MOI.set.(model, POI.ParameterValue(), p, 0.5)
     POI.update_parameters!(backend(model))
-    return nothing
+    return
 end
 
 function moi_add_sqf_variables_ctr(N::Int, M::Int)
@@ -145,8 +144,8 @@ function moi_add_sqf_variables_ctr(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:N])
-    @constraint(model, con[i=1:M], dot(x, x) >= 1)
-    return nothing
+    @constraint(model, con[i=1:M], x' * x >= 1)
+    return
 end
 
 function poi_add_sqf_variables_ctr(N::Int, M::Int)
@@ -159,8 +158,8 @@ function poi_add_sqf_variables_ctr(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:N])
-    @constraint(model, con[i=1:M], dot(x, x) >= 1)
-    return nothing
+    @constraint(model, con[i=1:M], x' * x >= 1)
+    return
 end
 
 function poi_add_sqf_variables_parameters_ctr(N::Int, M::Int)
@@ -173,9 +172,9 @@ function poi_add_sqf_variables_parameters_ctr(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
-    @constraint(model, con[i=1:M], dot(x, p) >= 1)
-    return nothing
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
+    @constraint(model, con[i=1:M], x' * p >= 1)
+    return
 end
 
 function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
@@ -188,11 +187,11 @@ function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
-    @constraint(model, con[i=1:M], dot(x, p) >= 1)
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
+    @constraint(model, con[i=1:M], x' * p >= 1)
     MOI.set.(model, POI.ParameterValue(), p, 0.5)
     POI.update_parameters!(backend(model))
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_ctr(N::Int, M::Int)
@@ -205,9 +204,9 @@ function poi_add_sqf_parameters_parameters_ctr(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
-    @constraint(model, con[i=1:M], dot(p, p) >= 1)
-    return nothing
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
+    @constraint(model, con[i=1:M], p' * p >= 1)
+    return
 end
 
 function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
@@ -220,11 +219,11 @@ function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
-    @constraint(model, con[i=1:M], dot(p, p) >= 1)
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
+    @constraint(model, con[i=1:M], p' * p >= 1)
     MOI.set.(model, POI.ParameterValue(), p, 0.5)
     POI.update_parameters!(backend(model))
-    return nothing
+    return
 end
 
 function moi_add_saf_obj(N::Int, M::Int)
@@ -236,7 +235,7 @@ function moi_add_saf_obj(N::Int, M::Int)
     )
     @variable(model, x[i=1:N])
     @objective(model, Min, sum(x))
-    return nothing
+    return
 end
 
 function poi_add_saf_obj(N::Int, M::Int)
@@ -252,7 +251,7 @@ function poi_add_saf_obj(N::Int, M::Int)
     for _ in 1:M
         @objective(model, Min, sum(x))
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_obj(N::Int, M::Int)
@@ -265,11 +264,11 @@ function poi_add_saf_variables_and_parameters_obj(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
         @objective(model, Min, sum(x) + sum(p))
     end
-    return nothing
+    return
 end
 
 function poi_add_saf_variables_and_parameters_obj_parameter_update(
@@ -285,7 +284,7 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
         @objective(model, Min, sum(x) + sum(p))
     end
@@ -293,7 +292,7 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
         MOI.set.(model, POI.ParameterValue(), p, 0.5)
         POI.update_parameters!(backend(model))
     end
-    return nothing
+    return
 end
 
 function moi_add_sqf_variables_obj(N::Int, M::Int)
@@ -305,9 +304,9 @@ function moi_add_sqf_variables_obj(N::Int, M::Int)
     )
     @variable(model, x[i=1:N])
     for _ in 1:M
-        @objective(model, Min, dot(x, x))
+        @objective(model, Min, x' * x)
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_obj(N::Int, M::Int)
@@ -321,9 +320,9 @@ function poi_add_sqf_variables_obj(N::Int, M::Int)
     )
     @variable(model, x[i=1:N])
     for _ in 1:M
-        @objective(model, Min, dot(x, x))
+        @objective(model, Min, x' * x)
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_obj(N::Int, M::Int)
@@ -336,11 +335,11 @@ function poi_add_sqf_variables_parameters_obj(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
-        @objective(model, Min, dot(x, p))
+        @objective(model, Min, x' * p)
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
@@ -353,15 +352,15 @@ function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
-        @objective(model, Min, dot(x, p))
+        @objective(model, Min, x' * p)
     end
     for _ in 1:M
         MOI.set.(model, POI.ParameterValue(), p, 0.5)
         POI.update_parameters!(backend(model))
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_obj(N::Int, M::Int)
@@ -374,11 +373,11 @@ function poi_add_sqf_parameters_parameters_obj(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
-        @objective(model, Min, dot(p, p))
+        @objective(model, Min, p' * p)
     end
-    return nothing
+    return
 end
 
 function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
@@ -391,15 +390,15 @@ function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
         ),
     )
     @variable(model, x[i=1:Int(N/2)])
-    @variable(model, p[i=1:Int(N/2)] in MOI.Parameter.(1))
+    @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     for _ in 1:M
-        @objective(model, Min, dot(p, p))
+        @objective(model, Min, p' * p)
     end
     for _ in 1:M
         MOI.set.(model, POI.ParameterValue(), p, 0.5)
         POI.update_parameters!(backend(model))
     end
-    return nothing
+    return
 end
 
 function run_benchmarks(N::Int, M::Int)
@@ -497,7 +496,7 @@ function run_benchmarks(N::Int, M::Int)
         "Update parameters in SQF objective with product of parameters on a POI.Optimizer.",
     )
     @btime poi_add_sqf_parameters_parameters_obj_parameter_update($N, $M)
-    return nothing
+    return
 end
 
 N = 10_000
diff --git a/benchmark/MOI_benchmarks.jl b/benchmark/run_benchmarks_pmedian.jl
similarity index 54%
rename from benchmark/MOI_benchmarks.jl
rename to benchmark/run_benchmarks_pmedian.jl
index 3dc91c22..c8ca1dbc 100644
--- a/benchmark/MOI_benchmarks.jl
+++ b/benchmark/run_benchmarks_pmedian.jl
@@ -3,25 +3,11 @@
 # Use of this source code is governed by an MIT-style license that can be found
 # in the LICENSE.md file or at https://opensource.org/licenses/MIT.
 
-push!(LOAD_PATH, "./src")
-using ParametricOptInterface
-using MathOptInterface
-using HiGHS
+import HiGHS
+import MathOptInterface as MOI
+import ParametricOptInterface as POI
 import Random
-#using SparseArrays
-using TimerOutputs
-
-const MOI = MathOptInterface
-const POI = ParametricOptInterface
-SOLVER = HiGHS
-
-if SOLVER == HiGHS
-    MAX_ITER_PARAM = "simplex_iteration_limit"
-elseif SOLVER == Gurobi
-    MAX_ITER_PARAM = "IterationLimit"
-elseif SOLVER == Xpress
-    MAX_ITER_PARAM = "LPITERLIMIT"
-end
+import TimerOutputs
 
 struct PMedianData
     num_facilities::Int
@@ -117,7 +103,7 @@ function generate_poi_problem(model, data::PMedianData, add_parameters::Bool)
     if add_parameters
         d, cd = MOI.add_constrained_variable(
             model,
-            MOI.Parameter(data.num_facilities),
+            MOI.Parameter{Float64}(data.num_facilities),
         )
     end
 
@@ -128,7 +114,7 @@ function generate_poi_problem(model, data::PMedianData, add_parameters::Bool)
                 MOI.ScalarAffineTerm.(1.0, vcat(facility_variables, d)),
                 0.0,
             ),
-            MOI.EqualTo{Float64}(0),
+            MOI.EqualTo{Float64}(0.0),
         )
     else
         MOI.add_constraint(
@@ -147,127 +133,54 @@ end
 function solve_moi(
     data::PMedianData,
     optimizer;
-    vector_version,
     params,
-    add_parameters = false,
+    add_parameters::Bool = false,
 )
-    model = optimizer()
+    model = MOI.instantiate(optimizer)
     for (param, value) in params
         MOI.set(model, param, value)
     end
-    @timeit "generate" x, y = if vector_version
-        generate_poi_problem_vector(model, data, add_parameters)
-    else
-        generate_poi_problem(model, data, add_parameters)
-    end
-    @timeit "solve" MOI.optimize!(model)
-    return MOI.get(model, MOI.ObjectiveValue())
-end
-
-function POI_OPTIMIZER()
-    return POI.Optimizer(SOLVER.Optimizer)
-end
-
-function solve_moi_loop(
-    data::PMedianData;
-    vector_version,
-    max_iters = Inf,
-    time_limit_sec = Inf,
-    loops,
-)
-    params = []
-    if isfinite(time_limit_sec)
-        push!(params, (MOI.TimeLimitSec(), time_limit_sec))
-    end
-    if isfinite(max_iters)
-        push!(params, (MOI.RawOptimizerAttribute(MAX_ITER_PARAM), max_iters))
-    end
-    push!(params, (MOI.Silent(), true))
-    s_type = vector_version ? "vector" : "scalar"
-
-    @timeit(
-        "$(SOLVER) MOI $(s_type)",
-        for _ in 1:loops
-            solve_moi(
-                data,
-                SOLVER.Optimizer();
-                vector_version = vector_version,
-                params = params,
-            )
-        end
+    TimerOutputs.@timeit(
+        "generate",
+        generate_poi_problem(model, data, add_parameters),
     )
+    TimerOutputs.@timeit "solve" MOI.optimize!(model)
+    return MOI.get(model, MOI.TerminationStatus())
 end
 
-function solve_poi_no_params_loop(
+function solve_moi_loop(
+    optimizer,
+    name,
     data::PMedianData;
-    vector_version,
     max_iters = Inf,
     time_limit_sec = Inf,
     loops,
+    kwargs...,
 )
-    params = []
+    params = Any[(MOI.Silent(), true)]
     if isfinite(time_limit_sec)
         push!(params, (MOI.TimeLimitSec(), time_limit_sec))
     end
     if isfinite(max_iters)
-        push!(params, (MOI.RawOptimizerAttribute(MAX_ITER_PARAM), max_iters))
-    end
-    push!(params, (MOI.Silent(), true))
-    s_type = vector_version ? "vector" : "scalar"
-    @timeit(
-        "$(SOLVER) POI NO PARAMS $(s_type)",
-        for _ in 1:loops
-            solve_moi(
-                data,
-                POI_OPTIMIZER;
-                vector_version = vector_version,
-                params = params,
-            )
-        end
-    )
-end
-
-function solve_poi_loop(
-    data::PMedianData;
-    vector_version,
-    max_iters = Inf,
-    time_limit_sec = Inf,
-    loops = 1,
-)
-    params = []
-    if isfinite(time_limit_sec)
-        push!(params, (MOI.TimeLimitSec(), time_limit_sec))
+        push!(
+            params,
+            (MOI.RawOptimizerAttribute("simplex_iteration_limit"), max_iters),
+        )
     end
-    if isfinite(max_iters)
-        push!(params, (MOI.RawOptimizerAttribute(MAX_ITER_PARAM), max_iters))
+    TimerOutputs.@timeit "$name" for _ in 1:loops
+        solve_moi(data, optimizer; params, kwargs...)
     end
-    push!(params, (MOI.Silent(), true))
-    s_type = vector_version ? "vector" : "scalar"
-
-    @timeit(
-        "$(SOLVER) POI $(s_type)",
-        for _ in 1:loops
-            solve_moi(
-                data,
-                POI_OPTIMIZER;
-                vector_version = vector_version,
-                params = params,
-                add_parameters = true,
-            )
-        end
-    )
+    return
 end
 
 function run_benchmark(;
     num_facilities,
     num_customers,
     num_locations,
-    time_limit_sec,
-    max_iters,
-    loops,
+    kwargs...,
 )
     Random.seed!(10)
-    reset_timer!()
+    TimerOutputs.reset_timer!()
     data = PMedianData(
         num_facilities,
         num_customers,
@@ -275,35 +188,21 @@ function run_benchmark(;
         rand(num_customers) .* num_locations,
     )
     GC.gc()
-    solve_moi_loop(
-        data,
-        vector_version = false,
-        max_iters = max_iters,
-        time_limit_sec = time_limit_sec,
-        loops = loops,
-    )
+    solve_moi_loop(HiGHS.Optimizer, "HiGHS MOI NO PARAMS", data; kwargs...)
     GC.gc()
-    solve_poi_no_params_loop(
-        data,
-        vector_version = false,
-        max_iters = max_iters,
-        time_limit_sec = time_limit_sec,
-        loops = loops,
-    )
+    solve_moi_loop("HiGHS POI NO PARAMS", data; kwargs...) do
+        return POI.Optimizer(HiGHS.Optimizer)
+    end
     GC.gc()
-    solve_poi_loop(
-        data,
-        vector_version = false,
-        max_iters = max_iters,
-        time_limit_sec = time_limit_sec,
-        loops = loops,
-    )
+    solve_moi_loop("HiGHS POI", data; add_parameters = true, kwargs...) do
+        return POI.Optimizer(HiGHS.Optimizer)
+    end
     GC.gc()
-    print_timer()
-    return println()
+    TimerOutputs.print_timer()
+    return
 end
 
-run_benchmark(
+run_benchmark(;
     num_facilities = 100,
     num_customers = 100,
     num_locations = 100,
@@ -312,7 +211,7 @@ run_benchmark(
     loops = 1,
 )
 
-run_benchmark(
+run_benchmark(;
     num_facilities = 100,
     num_customers = 100,
     num_locations = 100,
diff --git a/benchmark/run_benders_quantile_regression_benchmark.jl b/benchmark/run_benders_quantile_regression_benchmark.jl
index dec633fb..10eb6197 100644
--- a/benchmark/run_benders_quantile_regression_benchmark.jl
+++ b/benchmark/run_benders_quantile_regression_benchmark.jl
@@ -3,40 +3,22 @@
 # Use of this source code is governed by an MIT-style license that can be found
 # in the LICENSE.md file or at https://opensource.org/licenses/MIT.
 
-import Pkg
-Pkg.activate(@__DIR__)
-Pkg.instantiate()
-
-using ParametricOptInterface
-using MathOptInterface
-
-const POI = ParametricOptInterface
-const MOI = MathOptInterface
-
-using ParameterJuMP
 using JuMP
-
-using HiGHS
-const OPTIMIZER = HiGHS.Optimizer
 using TimerOutputs
 
-using LinearAlgebra
-using Random
+import HiGHS
+import MathOptInterface as MOI
+import ParameterJuMP
+import ParametricOptInterface as POI
+import Random
 
 const N_Candidates = 200
 const N_Observations = 2000
 const N_Nodes = 200
-
 const Observations = 1:N_Observations
 const Candidates = 1:N_Candidates
-const Nodes = 1:N_Nodes;
-
-#' Initialize a random number generator to keep results deterministic
-
-rng = Random.MersenneTwister(123);
-
-#' Building regressors (explanatory) sinusoids
-
+const Nodes = 1:N_Nodes
+const rng = Random.MersenneTwister(123)
 const X = zeros(N_Candidates, N_Observations)
 const time = [obs / N_Observations * 1 for obs in Observations]
 for obs in Observations, cand in Candidates
@@ -44,35 +26,23 @@ for obs in Observations, cand in Candidates
     f = cand
     X[cand, obs] = sin(2 * pi * f * t)
 end
-
-#' Define coefficients
-
 β = zeros(N_Candidates)
 for i in Candidates
     if rand(rng) <= (1 - i / N_Candidates)^2 && i <= 100
         β[i] = 4 * rand(rng) / i
     end
 end
-# println("First coefs: $(β[1:min(10, N_Candidates)])")
-
 const y = X' * β .+ 0.1 * randn(rng, N_Observations)
 
 function full_model_regression()
-    time_build = @elapsed begin # measure time to create a model
-
-        # initialize a optimization model
-        full_model = direct_model(OPTIMIZER)
-        MOI.set(full_model, MOI.Silent(), true)
-
-        # create optimization variables of the problem
+    time_build = @elapsed begin
+        full_model = direct_model(HiGHS.Optimizer)
+        set_silent(full_model)
         @variables(full_model, begin
             ɛ_up[Observations] >= 0
             ɛ_dw[Observations] >= 0
             β[1:N_Candidates]
-            # 0 <= β[Candidates] <= 8
         end)
-
-        # define constraints of the model
         @constraints(
             full_model,
             begin
@@ -82,26 +52,20 @@ function full_model_regression()
                 ɛ_dw[i] >= -sum(X[j, i] * β[j] for j in Candidates) + y[i]
             end
         )
-
-        # construct the objective function to be minimized
         @objective(
             full_model,
             Min,
             sum(ɛ_up[i] + ɛ_dw[i] for i in Observations)
         )
     end
-
-    # solve the problem
     time_solve = @elapsed optimize!(full_model)
-
     println(
         "First coefficients in solution: $(value.(β)[1:min(10, N_Candidates)])",
     )
     println("Objective value: $(objective_value(full_model))")
     println("Time in solve: $time_solve")
     println("Time in build: $time_build")
-
-    return nothing
+    return
 end
 
 function ObsSet(K)
@@ -110,52 +74,29 @@ function ObsSet(K)
 end
 
 function slave_model(PARAM, K)
-
-    # initialize the JuMP model
     slave = if PARAM == 0
-        # special constructor exported by ParameterJuMP
-        # to add the functionality to the model
-        Model(OPTIMIZER)
+        Model(HiGHS.Optimizer)
     elseif PARAM == 1
-        # POI constructor
-        direct_model(POI.Optimizer(OPTIMIZER()))
-        # Model(() -> POI.ParametricOptimizer(OPTIMIZER()))
+        direct_model(POI.Optimizer(HiGHS.Optimizer))
     else
-        # regular JuMP constructor
-        direct_model(OPTIMIZER())
+        direct_model(HiGHS.Optimizer())
     end
-    MOI.set(slave, MOI.Silent(), true)
-
-    # Define local optimization variables for norm-1 error
+    set_silent(slave)
     @variables(slave, begin
         ɛ_up[ObsSet(K)] >= 0
         ɛ_dw[ObsSet(K)] >= 0
     end)
-
-    # create the regression coefficient representation
     if PARAM == 0
-        # here is the main constructor of the Parameter JuMP packages
-        # It will create model *parameters* instead of variables
-        # Variables are added to the optimization model, while parameters
-        # are not. Parameters are merged with LP problem constants and do not
-        # increase the model dimensions.
-        @variable(slave, β[i=1:N_Candidates] == 0, Param())
+        @variable(slave, β[1:N_Candidates] == 0, ParameterJuMP.Param())
     elseif PARAM == 1
-        # Create parameters
-        @variable(slave, β[i=1:N_Candidates] in MOI.Parameter.(0.0))
+        @variable(slave, β[1:N_Candidates] in Parameter(0))
     else
-        # Create fixed variables
         @variables(slave, begin
             β[Candidates]
             β_fixed[1:N_Candidates] == 0
         end)
         @constraint(slave, β_fix[i in Candidates], β[i] == β_fixed[i])
     end
-
-    # create local constraints
-    # Note that *parameter* algebra is implemented just like variables
-    # algebra. We can multiply parameters by constants, add parameters,
-    # sum parameters and variables and so on.
     @constraints(
         slave,
         begin
@@ -165,160 +106,90 @@ function slave_model(PARAM, K)
             ɛ_dw[i] >= -sum(X[j, i] * β[j] for j in Candidates) + y[i]
         end
     )
-
-    # create local objective function
     @objective(slave, Min, sum(ɛ_up[i] + ɛ_dw[i] for i in ObsSet(K)))
-
-    # return the correct group of parameters
     return (slave, β)
 end
 
 function master_model(PARAM)
-    master = Model(OPTIMIZER)
+    master = Model(HiGHS.Optimizer)
+    set_silent(master)
     @variables(master, begin
         ɛ[Nodes] >= 0
         β[1:N_Candidates]
     end)
-    @objective(master, Min, sum(ɛ[i] for i in Nodes))
-    sol = zeros(N_Candidates)
-    return (master, ɛ, β, sol)
+    @objective(master, Min, sum(ɛ))
+    return (master, ɛ, β, zeros(N_Candidates))
 end
 
 function master_solve(PARAM, master_model)
-    model = master_model[1]
-    β = master_model[3]
+    model, _, β, _ = master_model
     optimize!(model)
     return (value.(β), objective_value(model))
 end
 
 function slave_solve(PARAM, model, master_solution)
-    β0 = master_solution[1]
-    slave = model[1]
-
-    # The first step is to fix the values given by the master problem
+    β0, _ = master_solution
+    slave, β = model
     @timeit "fix" if PARAM == 0
-        # ParameterJuMP: *parameters* can be set to new values and the optimization
-        # model will be automatically updated
-        β = model[2]
         set_value.(β, β0)
     elseif PARAM == 1
-        # POI: assigning new values to *parameters* and the optimization
-        # model will be automatically updated
-        β = model[2]
-        MOI.set.(slave, POI.ParameterValue(), β, β0)
+        set_parameter_value.(β, β0)
     else
-        # JuMP: it is also possible to fix variables to new values
-        β_fixed = slave[:β_fixed]
-        fix.(β_fixed, β0)
+        fix.(slave[:β_fixed], β0)
     end
-
-    # here the slave problem is solved
     @timeit "opt" optimize!(slave)
-
-    # query dual variables, which are sensitivities
-    # They represent the subgradient (almost a derivative)
-    # of the objective function for infinitesimal variations
-    # of the constants in the linear constraints
-    @timeit "dual" if PARAM == 0
-        # ParameterJuMP: we can query dual values of *parameters*
-        π = dual.(β)
+    @timeit "dual" π = if PARAM == 0
+        dual.(β)
     elseif PARAM == 1
-        # POI: we can query dual values of *parameters*
-        π = MOI.get.(slave, POI.ParameterDual(), β)
+        dual.(ParameterRef.(β))
     else
-        # or, in pure JuMP, we query the duals form
-        # constraints that fix the values of our regression
-        # coefficients
-        π = dual.(slave[:β_fix])
+        dual.(slave[:β_fix])
     end
-
-    # π2 = shadow_price.(β_fix)
-    # @show sum(π .- π2)
     obj = objective_value(slave)
-    rhs = obj - dot(π, β0)
+    rhs = obj - π' * β0
     return (rhs, π, obj)
 end
 
 function master_add_cut(PARAM, master_model, cut_info, node)
-    master = master_model[1]
-    ɛ = master_model[2]
-    β = master_model[3]
-
-    rhs = cut_info[1]
-    π = cut_info[2]
-
+    master, ɛ, β, _ = master_model
+    rhs, π, _ = cut_info
     @constraint(master, ɛ[node] >= sum(π[j] * β[j] for j in Candidates) + rhs)
+    return
 end
+
 function decomposed_model(PARAM; print_timer_outputs::Bool = true)
-    reset_timer!() # reset timer fo comparision
+    reset_timer!()
     time_init = @elapsed @timeit "Init" begin
-        # println("Initialize decomposed model")
-
-        # Create the master problem with no cuts
-        # println("Build master problem")
         @timeit "Master" master = master_model(PARAM)
-
-        # initialize solution for the regression coefficients in zero
-        # println("Build initial solution")
         @timeit "Sol" solution = (zeros(N_Candidates), Inf)
         best_sol = deepcopy(solution)
-
-        # Create the slave problems
-        # println("Build slave problems")
         @timeit "Slaves" slaves =
             [slave_model(PARAM, i) for i in Candidates]
-
-        # Save initial version of the slave problems and create
-        # the first set of cuts
-        # println("Build initial cuts")
         @timeit "Cuts" cuts =
             [slave_solve(PARAM, slaves[i], solution) for i in Candidates]
     end
-
-    UB = +Inf
-    LB = -Inf
-
-    # println("Initialize Iterative step")
+    LB, UB = -Inf, +Inf
     time_loop = @elapsed @timeit "Loop" for k in 1:80
-
-        # Add cuts generated from each slave problem to the master problem
         @timeit "add cuts" for i in Candidates
             master_add_cut(PARAM, master, cuts[i], i)
         end
-
-        # Solve the master problem with the new set of cuts
-        # Obtain new solution candidate for the regression coefficients
         @timeit "solve master" solution = master_solve(PARAM, master)
-
-        # Pass the new candidate solution to each of the slave problems
-        # Solve the slave problems and obtain cutting planes
-        # @show solution[2]
         @timeit "solve nodes" for i in Candidates
             cuts[i] = slave_solve(PARAM, slaves[i], solution)
         end
-
         LB = solution[2]
         new_UB = sum(cuts[i][3] for i in Candidates)
         if new_UB <= UB
             best_sol = deepcopy(solution)
         end
         UB = min(UB, new_UB)
-        # println("Iter = $k, LB = $LB, UB = $UB")
-
         if abs(UB - LB) / (abs(UB) + abs(LB)) < 0.05
-            # println("Converged!")
             break
         end
     end
-    # println(
-    #     "First coefficients in solution: $(solution[1][1:min(10, N_Candidates)])",
-    # )
-    # println("Objective value: $(solution[2])")
-    # println("Time in loop: $time_loop")
-    # println("Time in init: $time_init")
-
-    print_timer_outputs && print_timer()
-
+    if print_timer_outputs
+        print_timer()
+    end
     return best_sol[1]
 end
 
@@ -339,3 +210,5 @@ GC.gc()
 β3 = decomposed_model(2; print_timer_outputs = false);
 GC.gc()
 β3 = decomposed_model(2);
+
+nothing;