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Instance slay05m
Determine the optimal placement of a set of units with fixed width and length such that the Euclidean distance between their center point and a predefined "safety point" is minimized.
Formatsⓘ | ams gms lp mod nl osil pip py |
Primal Bounds (infeas ≤ 1e-08)ⓘ | |
Other points (infeas > 1e-08)ⓘ | |
Dual Boundsⓘ | 22664.67800000 (ALPHAECP) 22664.67846000 (ANTIGONE) 22664.67865000 (BARON) 22664.67865000 (BONMIN) 22664.67843000 (COUENNE) 22664.67865000 (CPLEX) 22664.67865000 (GUROBI) 22664.67865000 (LINDO) 22664.67865000 (SCIP) 22664.67865000 (SHOT) |
Referencesⓘ | Sawaya, Nicolas W, Reformulations, relaxations and cutting planes for generalized disjunctive programming, PhD thesis, Carnegie Mellon University, 2006. |
Sourceⓘ | SLay05M.gms from CMU-IBM MINLP solver project page |
Applicationⓘ | Layout |
Added to libraryⓘ | 28 Sep 2013 |
Problem typeⓘ | MBQP |
#Variablesⓘ | 70 |
#Binary Variablesⓘ | 40 |
#Integer Variablesⓘ | 0 |
#Nonlinear Variablesⓘ | 10 |
#Nonlinear Binary Variablesⓘ | 0 |
#Nonlinear Integer Variablesⓘ | 0 |
Objective Senseⓘ | min |
Objective typeⓘ | quadratic |
Objective curvatureⓘ | convex |
#Nonzeros in Objectiveⓘ | 30 |
#Nonlinear Nonzeros in Objectiveⓘ | 10 |
#Constraintsⓘ | 90 |
#Linear Constraintsⓘ | 90 |
#Quadratic Constraintsⓘ | 0 |
#Polynomial Constraintsⓘ | 0 |
#Signomial Constraintsⓘ | 0 |
#General Nonlinear Constraintsⓘ | 0 |
Operands in Gen. Nonlin. Functionsⓘ | |
Constraints curvatureⓘ | linear |
#Nonzeros in Jacobianⓘ | 280 |
#Nonlinear Nonzeros in Jacobianⓘ | 0 |
#Nonzeros in (Upper-Left) Hessian of Lagrangianⓘ | 10 |
#Nonzeros in Diagonal of Hessian of Lagrangianⓘ | 10 |
#Blocks in Hessian of Lagrangianⓘ | 10 |
Minimal blocksize in Hessian of Lagrangianⓘ | 1 |
Maximal blocksize in Hessian of Lagrangianⓘ | 1 |
Average blocksize in Hessian of Lagrangianⓘ | 1.0 |
#Semicontinuitiesⓘ | 0 |
#Nonlinear Semicontinuitiesⓘ | 0 |
#SOS type 1ⓘ | 0 |
#SOS type 2ⓘ | 0 |
Minimal coefficientⓘ | 1.0000e+00 |
Maximal coefficientⓘ | 3.9000e+02 |
Infeasibility of initial pointⓘ | 2.5 |
Sparsity Jacobianⓘ | |
Sparsity Hessian of Lagrangianⓘ |
$offlisting * * Equation counts * Total E G L N X C B * 91 11 40 40 0 0 0 0 * * Variable counts * x b i s1s s2s sc si * Total cont binary integer sos1 sos2 scont sint * 71 31 40 0 0 0 0 0 * FX 0 * * Nonzero counts * Total const NL DLL * 311 301 10 0 * * Solve m using MINLP minimizing objvar; Variables x1,x2,x3,x4,x5,x6,x7,x8,x9,x10,b11,b12,b13,b14,b15,b16,b17,b18,b19 ,b20,b21,b22,b23,b24,b25,b26,b27,b28,b29,b30,b31,b32,b33,b34,b35,b36 ,b37,b38,b39,b40,b41,b42,b43,b44,b45,b46,b47,b48,b49,b50,x51,x52,x53 ,x54,x55,x56,x57,x58,x59,x60,x61,x62,x63,x64,x65,x66,x67,x68,x69,x70 ,objvar; Positive Variables x51,x52,x53,x54,x55,x56,x57,x58,x59,x60,x61,x62,x63,x64 ,x65,x66,x67,x68,x69,x70; Binary Variables b11,b12,b13,b14,b15,b16,b17,b18,b19,b20,b21,b22,b23,b24,b25 ,b26,b27,b28,b29,b30,b31,b32,b33,b34,b35,b36,b37,b38,b39,b40,b41,b42 ,b43,b44,b45,b46,b47,b48,b49,b50; Equations e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12,e13,e14,e15,e16,e17,e18,e19 ,e20,e21,e22,e23,e24,e25,e26,e27,e28,e29,e30,e31,e32,e33,e34,e35,e36 ,e37,e38,e39,e40,e41,e42,e43,e44,e45,e46,e47,e48,e49,e50,e51,e52,e53 ,e54,e55,e56,e57,e58,e59,e60,e61,e62,e63,e64,e65,e66,e67,e68,e69,e70 ,e71,e72,e73,e74,e75,e76,e77,e78,e79,e80,e81,e82,e83,e84,e85,e86,e87 ,e88,e89,e90,e91; e1.. -(150*(sqr((-4) + x1) + sqr((-10) + x6)) + 390*(sqr((-10) + x2) + sqr((-15 ) + x7)) + 240*(sqr((-7) + x3) + sqr((-9) + x8)) + 70*(sqr((-3) + x4) + sqr((-3) + x9)) + 165*(sqr((-20) + x5) + sqr((-17) + x10))) - 300*x51 - 240*x52 - 210*x53 - 140*x54 - 100*x55 - 150*x56 - 220*x57 - 120*x58 - 300*x59 - 100*x60 - 300*x61 - 240*x62 - 210*x63 - 140*x64 - 100*x65 - 150*x66 - 220*x67 - 120*x68 - 300*x69 - 100*x70 + objvar =E= 0; e2.. - x1 + x2 + x51 =G= 0; e3.. - x1 + x3 + x52 =G= 0; e4.. - x1 + x4 + x53 =G= 0; e5.. - x1 + x5 + x54 =G= 0; e6.. - x2 + x3 + x55 =G= 0; e7.. - x2 + x4 + x56 =G= 0; e8.. - x2 + x5 + x57 =G= 0; e9.. - x3 + x4 + x58 =G= 0; e10.. - x3 + x5 + x59 =G= 0; e11.. - x4 + x5 + x60 =G= 0; e12.. x1 - x2 + x51 =G= 0; e13.. x1 - x3 + x52 =G= 0; e14.. x1 - x4 + x53 =G= 0; e15.. x1 - x5 + x54 =G= 0; e16.. x2 - x3 + x55 =G= 0; e17.. x2 - x4 + x56 =G= 0; e18.. x2 - x5 + x57 =G= 0; e19.. x3 - x4 + x58 =G= 0; e20.. x3 - x5 + x59 =G= 0; e21.. x4 - x5 + x60 =G= 0; e22.. - x6 + x7 + x61 =G= 0; e23.. - x6 + x8 + x62 =G= 0; e24.. - x6 + x9 + x63 =G= 0; e25.. - x6 + x10 + x64 =G= 0; e26.. - x7 + x8 + x65 =G= 0; e27.. - x7 + x9 + x66 =G= 0; e28.. - x7 + x10 + x67 =G= 0; e29.. - x8 + x9 + x68 =G= 0; e30.. - x8 + x10 + x69 =G= 0; e31.. - x9 + x10 + x70 =G= 0; e32.. x6 - x7 + x61 =G= 0; e33.. x6 - x8 + x62 =G= 0; e34.. x6 - x9 + x63 =G= 0; e35.. x6 - x10 + x64 =G= 0; e36.. x7 - x8 + x65 =G= 0; e37.. x7 - x9 + x66 =G= 0; e38.. x7 - x10 + x67 =G= 0; e39.. x8 - x9 + x68 =G= 0; e40.. x8 - x10 + x69 =G= 0; e41.. x9 - x10 + x70 =G= 0; e42.. x1 - x2 + 30*b11 =L= 24; e43.. x1 - x3 + 30*b12 =L= 26; e44.. x1 - x4 + 30*b13 =L= 26.5; e45.. x1 - x5 + 30*b14 =L= 25.5; e46.. x2 - x3 + 30*b15 =L= 25; e47.. x2 - x4 + 30*b16 =L= 25.5; e48.. x2 - x5 + 30*b17 =L= 24.5; e49.. x3 - x4 + 30*b18 =L= 27.5; e50.. x3 - x5 + 30*b19 =L= 26.5; e51.. x4 - x5 + 30*b20 =L= 27; e52.. - x1 + x2 + 30*b21 =L= 24; e53.. - x1 + x3 + 30*b22 =L= 26; e54.. - x1 + x4 + 30*b23 =L= 26.5; e55.. - x1 + x5 + 30*b24 =L= 25.5; e56.. - x2 + x3 + 30*b25 =L= 25; e57.. - x2 + x4 + 30*b26 =L= 25.5; e58.. - x2 + x5 + 30*b27 =L= 24.5; e59.. - x3 + x4 + 30*b28 =L= 27.5; e60.. - x3 + x5 + 30*b29 =L= 26.5; e61.. - x4 + x5 + 30*b30 =L= 27; e62.. x6 - x7 + 30*b31 =L= 24.5; e63.. x6 - x8 + 30*b32 =L= 25.5; e64.. x6 - x9 + 30*b33 =L= 25.5; e65.. x6 - x10 + 30*b34 =L= 25; e66.. x7 - x8 + 30*b35 =L= 26; e67.. x7 - x9 + 30*b36 =L= 26; e68.. x7 - x10 + 30*b37 =L= 25.5; e69.. x8 - x9 + 30*b38 =L= 27; e70.. x8 - x10 + 30*b39 =L= 26.5; e71.. x9 - x10 + 30*b40 =L= 26.5; e72.. - x6 + x7 + 30*b41 =L= 24.5; e73.. - x6 + x8 + 30*b42 =L= 25.5; e74.. - x6 + x9 + 30*b43 =L= 25.5; e75.. - x6 + x10 + 30*b44 =L= 25; e76.. - x7 + x8 + 30*b45 =L= 26; e77.. - x7 + x9 + 30*b46 =L= 26; e78.. - x7 + x10 + 30*b47 =L= 25.5; e79.. - x8 + x9 + 30*b48 =L= 27; e80.. - x8 + x10 + 30*b49 =L= 26.5; e81.. - x9 + x10 + 30*b50 =L= 26.5; e82.. b11 + b21 + b31 + b41 =E= 1; e83.. b12 + b22 + b32 + b42 =E= 1; e84.. b13 + b23 + b33 + b43 =E= 1; e85.. b14 + b24 + b34 + b44 =E= 1; e86.. b15 + b25 + b35 + b45 =E= 1; e87.. b16 + b26 + b36 + b46 =E= 1; e88.. b17 + b27 + b37 + b47 =E= 1; e89.. b18 + b28 + b38 + b48 =E= 1; e90.. b19 + b29 + b39 + b49 =E= 1; e91.. b20 + b30 + b40 + b50 =E= 1; * set non-default bounds x1.lo = 2.5; x1.up = 27.5; x2.lo = 3.5; x2.up = 26.5; x3.lo = 1.5; x3.up = 28.5; x4.lo = 1; x4.up = 29; x5.lo = 2; x5.up = 28; x6.lo = 3; x6.up = 27; x7.lo = 2.5; x7.up = 27.5; x8.lo = 1.5; x8.up = 28.5; x9.lo = 1.5; x9.up = 28.5; x10.lo = 2; x10.up = 28; Model m / all /; m.limrow=0; m.limcol=0; m.tolproj=0.0; $if NOT '%gams.u1%' == '' $include '%gams.u1%' $if not set MINLP $set MINLP MINLP Solve m using %MINLP% minimizing objvar;
Last updated: 2024-12-17 Git hash: 8eaceb91