Update

Author: odow

papers/Dowson_et_al_2026/final_results.out

@@ -1,8 +1,8 @@
-2 & 200 & \texttt{Dichotomy} & Gurobi & 34.7 & 69.0 & 1 & 90 \\
-2 & 200 & \texttt{Dichotomy} & HiGHS & 34.9 & 3571.1 & 125 & 98 \\
+2 & 200 & \texttt{Dichotomy} & Gurobi & 34.7 & 68.9 & 1 & 88 \\
+2 & 200 & \texttt{Dichotomy} & HiGHS & 34.9 & 68.1 & 6 & 98 \\
 2 & 200 & \texttt{EpsilonConstraint} & Gurobi & 405.4 & 813.8 & 29 & 99 \\
 2 & 200 & \texttt{EpsilonConstraint} & HiGHS & 405.4 & 813.8 & 351 & 100 \\
-2 & 200 & \texttt{TambyVanderpooten} & Gurobi & 405.4 & 818.2 & 30 & 99 \\
-2 & 200 & \texttt{TambyVanderpooten} & HiGHS & 405.4 & 818.6 & 365 & 100 \\
-3 & 100 & \texttt{TambyVanderpooten} & Gurobi & 3341.6 & 12717.1 & 583 & 97 \\
-4 & 50 & \texttt{TambyVanderpooten} & Gurobi & 1799.4 & 13699.7 & 506 & 69 \\
+2 & 200 & \texttt{TambyVanderpooten} & Gurobi & 405.4 & 818.2 & 31 & 99 \\
+2 & 200 & \texttt{TambyVanderpooten} & HiGHS & 405.4 & 818.6 & 366 & 100 \\
+3 & 100 & \texttt{TambyVanderpooten} & Gurobi & 4090.0 & 14724.4 & 673 & 97 \\
+4 & 50 & \texttt{TambyVanderpooten} & Gurobi & 2240.1 & 20570.2 & 1042 & 68 \\

papers/Dowson_et_al_2026/main.jl

@@ -28,7 +28,7 @@ function solve_tamby_mokp(;
     C = reduce(vcat, [Float64.(x.args) for x in Meta.parse(lines[4]).args]')
     w = Meta.parse(lines[5]).args
     model = Model(() -> MOA.Optimizer(optimizer))
-    set_time_limit_sec(model, time_limit)
+    # set_time_limit_sec(model, time_limit)
     if silent
         set_silent(model)
     end
@@ -70,6 +70,9 @@ results_filename = "results.log"
 results = Any[]
 for ((p, n), (algorithms, solvers)) in TESTSETS, instance in 1:10
     for alg in algorithms, solver in solvers
+	if !((p, instance) in [(4, 8)])
+		continue
+	end
         algorithm, optimizer = ALGORITHMS[alg], OPTIMIZERS[solver]
         println("Running: p-$(p)_n-$(n)_$(instance) :: $alg :: $solver")
         ret = solve_tamby_mokp(; p, n, instance, optimizer, algorithm)