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‎docs/RULES_hs85_hs89.md‎

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# OptimizationProblems.jl Rules — HS85 & HS89 Example
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| Rule | HS85 | HS89 | How to Check |
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|------|------|------|--------------|
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| File Structure | src/ADNLPProblems/hs85.jl, src/PureJuMP/hs85.jl, src/Meta/hs85.md | src/ADNLPProblems/hs89.jl, src/PureJuMP/hs89.jl, src/Meta/hs89.md | Check for all three files per problem |
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| Header | HS-style header: source, classification, implementation date | Same | Parse header comments for required fields |
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| Mathematical Expressions | All intermediates, constraints, objective explicit, match paper | Same | Compare expressions to paper and extracted JSON |
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| Variable Bounds | Explicit bounds and x0 in ADNLP and PureJuMP | Same | Check for bounds and x0 in both files |
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| Metadata | References, classification, origin, scalable, etc. in Meta file | Same | Parse Meta file for required metadata |
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| Naming | hs85.jl, hs85_jump.jl, hs85.md | hs89.jl, hs89_jump.jl, hs89.md | Check file/function names |
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| Allocation | Constraint function minimizes allocations (relaxed for complex) | Same | Run allocation test or allow allocation |
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| Ipopt Solve | Problem solves with Ipopt (PureJuMP) | Same | Run Ipopt solver and check for solution |
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| Reviewer Markdown | Summary, PDF screenshot, extraction uncertainties, test results | Same | Generate reviewer markdown file |
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| Duplication | No duplicate (by name, structure, metadata) | Same | Check for similar names/metadata |
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| Traceability | Origin clear and referenced in header/Meta | Same | Check Meta/header |
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| Scalability | Marked if scalable (not for hs85/hs89) | Same | Check Meta/implementation |
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| Multiple Problems | One PDF = one problem (for hs85/hs89) | Same | Allow multiple if needed |
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| Uncertainty | Warn if extraction unclear (not for hs85/hs89) | Same | Parse extraction JSON for uncertainties |
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---
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This table is tailored to HS85 and HS89. Use as a checklist for similar problems and PRs.

‎docs/check_rules.jl‎

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# Script to check OptimizationProblems.jl rules for HS85/HS89
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using JSON
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function check_problem(problem::String)
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result = Dict()
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# File structure
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result["ADNLP"] = isfile("src/ADNLPProblems/$problem.jl")
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result["PureJuMP"] = isfile("src/PureJuMP/$problem.jl")
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result["Meta"] = isfile("src/Meta/$problem.md")
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# Header
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header_ok = false
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if result["ADNLP"]
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header = readlines("src/ADNLPProblems/$problem.jl")[1:10]
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header_ok = any(occursin("Hock and Schittkowski", h) for h in header)
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end
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result["Header"] = header_ok
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# Bounds/x0
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bounds_ok = false
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if result["ADNLP"]
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file = String(read("src/ADNLPProblems/$problem.jl"))
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bounds_ok = occursin("lvar", file) && occursin("uvar", file) && occursin("x0", file)
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end
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result["Bounds"] = bounds_ok
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# Metadata
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meta_ok = false
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if result["Meta"]
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meta = String(read("src/Meta/$problem.md"))
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meta_ok = occursin("Source", meta) && occursin("classification", meta)
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end
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result["Metadata"] = meta_ok
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# Allocation (relaxed)
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result["Allocation"] = false
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# Ipopt solve (not checked here)
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result["IpoptSolve"] = "manual"
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# Reviewer markdown
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result["ReviewerMarkdown"] = isfile("docs/review_$problem.md")
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return result
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end
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function main()
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problems = ["hs85", "hs89"]
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results = Dict()
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for p in problems
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results[p] = check_problem(p)
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end
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println(JSON.json(results))
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end
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main()

‎docs/extract_hs85.json‎

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{
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"problem": "hs85",
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"source": "Hock and Schittkowski, Problem 85",
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"variables": ["x1", "x2", "x3", "x4", "x5"],
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"bounds": {
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"lvar": [704.4148, 68.6, 0.0, 193.0, 25.0],
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"uvar": [906.3855, 288.88, 134.75, 287.0966, 84.1988],
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"x0": [900.0, 80.0, 115.0, 267.0, 27.0]
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},
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"objective": "-5.843e-7 * y17 + 1.17e-4 * y14 + 2.358e-5 * y13 + 1.502e-6 * y16 + 0.0321 * y12 + 0.004324 * y5 + 1e-4 * c15 / c16 + 37.48 * y2 / c12 + 0.1365",
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"constraints": [
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"1.5 * x2 - x3 >= 0",
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"y1 - 213.1 >= 0",
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"405.23 - y1 >= 0",
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"y2 - a2 >= 0",
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"y3 - a3 >= 0",
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"y4 - a4 >= 0",
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"y5 - a5 >= 0",
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"y6 - a6 >= 0",
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"y7 - a7 >= 0",
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"y8 - a8 >= 0",
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"y9 - a9 >= 0",
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"y10 - a10 >= 0",
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"y11 - a11 >= 0",
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"y12 - a12 >= 0",
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"y13 - a13 >= 0",
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"y14 - a14 >= 0",
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"y15 - a15 >= 0",
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"y16 - a16 >= 0",
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"y17 - a17 >= 0",
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"b2 - y2 >= 0",
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"b3 - y3 >= 0",
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"b4 - y4 >= 0",
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"b5 - y5 >= 0",
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"b6 - y6 >= 0",
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"b7 - y7 >= 0",
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"b8 - y8 >= 0",
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"b9 - y9 >= 0",
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"b10 - y10 >= 0",
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"b11 - y11 >= 0",
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"b12 - y12 >= 0",
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"b13 - y13 >= 0",
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"b14 - y14 >= 0",
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"b15 - y15 >= 0",
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"b16 - y16 >= 0",
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"b17 - y17 >= 0",
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"y4 - (0.28 / 0.72) * y5 >= 0",
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"21 - 3496 * y2 / c12 >= 0",
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"62212 / c17 - 110.6 - y1 >= 0",
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"x1 - lvar1 >= 0",
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"x2 - lvar2 >= 0",
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"x3 - lvar3 >= 0",
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"x4 - lvar4 >= 0",
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"x5 - lvar5 >= 0",
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"uvar1 - x1 >= 0",
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"uvar2 - x2 >= 0",
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"uvar3 - x3 >= 0",
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"uvar4 - x4 >= 0",
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"uvar5 - x5 >= 0"
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],
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"metadata": {
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"classification": "QGR-P1-(1,...,6)",
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"implementation": "AI/JSO, 03/2026"
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},
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"uncertainties": []
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}

‎docs/extract_hs89.json‎

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{
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"problem": "hs89",
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"source": "Hock and Schittkowski, Problem 89",
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"variables": ["x1", "x2", "x3"],
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"bounds": {
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"lvar": "none",
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"uvar": "none",
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"x0": "none"
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},
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"objective": "sum_{j=1}^{30} A_j * rho_j(x)\nwhere rho_j(x) = - (exp(-mu_j^2 * r) + 2*exp(-mu_j^2*(x2^2 + x3^2)) + 2*exp(-mu_j^2*x3^2) + 1) / mu_j^2\nr = x1^2 + x2^2 + x3^2\nA_j = 2*sin(mu_j)/(mu_j + sin(mu_j)*cos(mu_j))\nmu_j: first 30 positive roots of tan(mu) = mu",
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"constraints": [
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"c(x) = termA + termB - 2/15 = 0",
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"termA = sum_{j=1}^{30} A_j^2 * rho_j(x)^2 * (sin(2*mu_j)/(2*mu_j) + 1)/2",
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"termB = sum_{i=1}^{29} sum_{j=i+1}^{30} A_i * A_j * rho_i(x) * rho_j(x) * (sin(mu_i+mu_j)/(mu_i+mu_j) + sin(mu_i-mu_j)/(mu_i-mu_j))"
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],
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"metadata": {
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"classification": "QGR-P1-(1,...,6)",
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"implementation": "AI/JSO, 03/2026"
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},
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"uncertainties": []
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}

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