Closed chkwon closed 8 years ago
The model creation seems have bugs and errors.
The solution to transmcp.gms
transmcp.gms
---- VAR w shadow price at supply node i LOWER LEVEL UPPER MARGINAL seattle . . +INF 4.5931E-6 san-diego . . +INF 50.000 ---- VAR p shadow price at demand node j LOWER LEVEL UPPER MARGINAL new-york . 0.225 +INF 2.1987E-8 chicago . 0.153 +INF 6.5960E-8 topeka . 0.126 +INF . ---- VAR x shipment quantities in cases LOWER LEVEL UPPER MARGINAL seattle .new-york . 50.000 +INF . seattle .chicago . 300.000 +INF . seattle .topeka . . +INF 0.036 san-diego.new-york . 275.000 +INF . san-diego.chicago . . +INF 0.009 san-diego.topeka . 275.000 +INF .
The entire report:
Executed on neos-4.neos-server.org GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 1 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) C o m p i l a t i o n COMPILATION TIME = 0.000 SECONDS 3 MB 24.5.6 r55090 LEX-LEG GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 2 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Model Statistics SOLVE fixedqty Using MCP From line 84 MODEL STATISTICS BLOCKS OF EQUATIONS 3 SINGLE EQUATIONS 11 BLOCKS OF VARIABLES 3 SINGLE VARIABLES 11 NON ZERO ELEMENTS 24 NON LINEAR N-Z 0 DERIVATIVE POOL 20 CONSTANT POOL 16 CODE LENGTH 0 GENERATION TIME = 0.001 SECONDS 4 MB 24.5.6 r55090 LEX-LEG EXECUTION TIME = 0.002 SECONDS 4 MB 24.5.6 r55090 LEX-LEG GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 3 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Solution Report SOLVE fixedqty Using MCP From line 84 S O L V E S U M M A R Y MODEL fixedqty TYPE MCP SOLVER PATH FROM LINE 84 **** SOLVER STATUS 1 Normal Completion **** MODEL STATUS 1 Optimal RESOURCE USAGE, LIMIT 0.008 1000.000 ITERATION COUNT, LIMIT 30 2000000000 EVALUATION ERRORS 0 0 11 row/cols, 24 non-zeros, 19.83% dense. Path 4.7.03 (Fri Nov 27 05:18:03 2015) Written by Todd Munson, Steven Dirkse, and Michael Ferris INITIAL POINT STATISTICS Maximum of X. . . . . . . . . . 1.0000e+00 var: (w(seattle)) Maximum of F. . . . . . . . . . 6.0000e+02 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 1.0000e+00 eqn: (supply(seattle)) var: (x(seattle,new-york)) INITIAL JACOBIAN NORM STATISTICS Maximum Row Norm. . . . . . . . 3.0000e+00 eqn: (supply(seattle)) Minimum Row Norm. . . . . . . . 2.0000e+00 eqn: (profit(seattle,new-york)) Maximum Column Norm . . . . . . 3.0000e+00 var: (w(seattle)) Minimum Column Norm . . . . . . 2.0000e+00 var: (x(seattle,new-york)) FINAL STATISTICS Inf-Norm of Complementarity . . 1.5198e-08 eqn: (profit(seattle,chicago)) Inf-Norm of Normal Map. . . . . 6.5960e-08 eqn: (fxdemand(chicago)) Inf-Norm of Minimum Map . . . . 6.5960e-08 eqn: (fxdemand(chicago)) Inf-Norm of Fischer Function. . 6.5960e-08 eqn: (fxdemand(chicago)) Inf-Norm of Grad Fischer Fcn. . 6.5960e-08 eqn: (profit(seattle,chicago)) Two-Norm of Grad Fischer Fcn. . 9.8327e-08 FINAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 5.0000e+01 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 1.0000e+00 eqn: (supply(seattle)) var: (x(seattle,new-york)) ---- EQU profit zero profit conditions LOWER LEVEL UPPER MARGINAL seattle .new-york -0.225 -0.225 +INF 50.000 seattle .chicago -0.153 -0.153 +INF 300.000 seattle .topeka -0.162 -0.126 +INF . san-diego.new-york -0.225 -0.225 +INF 275.000 san-diego.chicago -0.162 -0.153 +INF . san-diego.topeka -0.126 -0.126 +INF 275.000 ---- EQU supply supply limit at plant i LOWER LEVEL UPPER MARGINAL seattle -350.000 -350.000 +INF . san-diego -600.000 -550.000 +INF . ---- EQU fxdemand fixed demand at market j LOWER LEVEL UPPER MARGINAL new-york 325.000 325.000 +INF 0.225 chicago 300.000 300.000 +INF 0.153 topeka 275.000 275.000 +INF 0.126 ---- VAR w shadow price at supply node i LOWER LEVEL UPPER MARGINAL seattle . . +INF 4.5931E-6 san-diego . . +INF 50.000 ---- VAR p shadow price at demand node j LOWER LEVEL UPPER MARGINAL new-york . 0.225 +INF 2.1987E-8 chicago . 0.153 +INF 6.5960E-8 topeka . 0.126 +INF . ---- VAR x shipment quantities in cases LOWER LEVEL UPPER MARGINAL seattle .new-york . 50.000 +INF . seattle .chicago . 300.000 +INF . seattle .topeka . . +INF 0.036 san-diego.new-york . 275.000 +INF . san-diego.chicago . . +INF 0.009 san-diego.topeka . 275.000 +INF . **** REPORT SUMMARY : 0 NONOPT 0 INFEASIBLE 0 UNBOUNDED 0 REDEFINED 0 ERRORS GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 4 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Model Statistics SOLVE equilqty Using MCP From line 93 MODEL STATISTICS BLOCKS OF EQUATIONS 3 SINGLE EQUATIONS 11 BLOCKS OF VARIABLES 3 SINGLE VARIABLES 11 NON ZERO ELEMENTS 27 NON LINEAR N-Z 3 DERIVATIVE POOL 20 CONSTANT POOL 24 CODE LENGTH 28 GENERATION TIME = 0.002 SECONDS 3 MB 24.5.6 r55090 LEX-LEG EXECUTION TIME = 0.003 SECONDS 3 MB 24.5.6 r55090 LEX-LEG GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 5 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Solution Report SOLVE equilqty Using MCP From line 93 S O L V E S U M M A R Y MODEL equilqty TYPE MCP SOLVER PATH FROM LINE 93 **** SOLVER STATUS 1 Normal Completion **** MODEL STATUS 1 Optimal RESOURCE USAGE, LIMIT 0.003 1000.000 ITERATION COUNT, LIMIT 0 2000000000 EVALUATION ERRORS 0 0 11 row/cols, 27 non-zeros, 22.31% dense. Path 4.7.03 (Fri Nov 27 05:18:03 2015) Written by Todd Munson, Steven Dirkse, and Michael Ferris INITIAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 5.0000e+01 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 4.3651e+03 eqn: (prdemand(topeka)) var: (p(topeka)) INITIAL JACOBIAN NORM STATISTICS Maximum Row Norm. . . . . . . . 4.3671e+03 eqn: (prdemand(topeka)) Minimum Row Norm. . . . . . . . 2.0000e+00 eqn: (profit(seattle,new-york)) Maximum Column Norm . . . . . . 4.3671e+03 var: (p(topeka)) Minimum Column Norm . . . . . . 2.0000e+00 var: (x(seattle,new-york)) FINAL STATISTICS Inf-Norm of Complementarity . . 1.5198e-08 eqn: (profit(seattle,chicago)) Inf-Norm of Normal Map. . . . . 6.5960e-08 eqn: (prdemand(chicago)) Inf-Norm of Minimum Map . . . . 6.5960e-08 eqn: (prdemand(chicago)) Inf-Norm of Fischer Function. . 6.5960e-08 eqn: (prdemand(chicago)) Inf-Norm of Grad Fischer Fcn. . 1.5520e-04 eqn: (prdemand(chicago)) Two-Norm of Grad Fischer Fcn. . 1.6235e-04 FINAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 5.0000e+01 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 4.3651e+03 eqn: (prdemand(topeka)) var: (p(topeka)) ---- EQU profit zero profit conditions LOWER LEVEL UPPER MARGINAL seattle .new-york -0.225 -0.225 +INF 50.000 seattle .chicago -0.153 -0.153 +INF 300.000 seattle .topeka -0.162 -0.126 +INF . san-diego.new-york -0.225 -0.225 +INF 275.000 san-diego.chicago -0.162 -0.153 +INF . san-diego.topeka -0.126 -0.126 +INF 275.000 ---- EQU supply supply limit at plant i LOWER LEVEL UPPER MARGINAL seattle -350.000 -350.000 +INF . san-diego -600.000 -550.000 +INF . ---- EQU prdemand price-responsive demand at market j LOWER LEVEL UPPER MARGINAL new-york . 2.1987E-8 +INF 0.225 chicago . 6.5960E-8 +INF 0.153 topeka . . +INF 0.126 ---- VAR w shadow price at supply node i LOWER LEVEL UPPER MARGINAL seattle . . +INF 4.5931E-6 san-diego . . +INF 50.000 ---- VAR p shadow price at demand node j LOWER LEVEL UPPER MARGINAL new-york . 0.225 +INF 2.1987E-8 chicago . 0.153 +INF 6.5960E-8 topeka . 0.126 +INF . ---- VAR x shipment quantities in cases LOWER LEVEL UPPER MARGINAL seattle .new-york . 50.000 +INF . seattle .chicago . 300.000 +INF . seattle .topeka . . +INF 0.036 san-diego.new-york . 275.000 +INF . san-diego.chicago . . +INF 0.009 san-diego.topeka . 275.000 +INF . **** REPORT SUMMARY : 0 NONOPT 0 INFEASIBLE 0 UNBOUNDED 0 REDEFINED 0 ERRORS GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 6 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Model Statistics SOLVE fixedqty Using MCP From line 100 MODEL STATISTICS BLOCKS OF EQUATIONS 3 SINGLE EQUATIONS 11 BLOCKS OF VARIABLES 3 SINGLE VARIABLES 11 NON ZERO ELEMENTS 24 NON LINEAR N-Z 0 DERIVATIVE POOL 20 CONSTANT POOL 16 CODE LENGTH 0 GENERATION TIME = 0.002 SECONDS 3 MB 24.5.6 r55090 LEX-LEG EXECUTION TIME = 0.003 SECONDS 3 MB 24.5.6 r55090 LEX-LEG GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 7 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Solution Report SOLVE fixedqty Using MCP From line 100 S O L V E S U M M A R Y MODEL fixedqty TYPE MCP SOLVER PATH FROM LINE 100 **** SOLVER STATUS 1 Normal Completion **** MODEL STATUS 1 Optimal RESOURCE USAGE, LIMIT 0.003 1000.000 ITERATION COUNT, LIMIT 1 2000000000 EVALUATION ERRORS 0 0 11 row/cols, 24 non-zeros, 19.83% dense. Path 4.7.03 (Fri Nov 27 05:18:03 2015) Written by Todd Munson, Steven Dirkse, and Michael Ferris INITIAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 5.0000e+01 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 1.0000e+00 eqn: (supply(seattle)) var: (x(seattle,new-york)) INITIAL JACOBIAN NORM STATISTICS Maximum Row Norm. . . . . . . . 3.0000e+00 eqn: (supply(seattle)) Minimum Row Norm. . . . . . . . 2.0000e+00 eqn: (profit(seattle,new-york)) Maximum Column Norm . . . . . . 3.0000e+00 var: (w(seattle)) Minimum Column Norm . . . . . . 2.0000e+00 var: (x(seattle,new-york)) FINAL STATISTICS Inf-Norm of Complementarity . . 8.6098e-09 eqn: (profit(seattle,chicago)) Inf-Norm of Normal Map. . . . . 2.8699e-11 eqn: (profit(seattle,chicago)) Inf-Norm of Minimum Map . . . . 2.8706e-11 eqn: (profit(seattle,chicago)) Inf-Norm of Fischer Function. . 2.8699e-11 eqn: (profit(seattle,chicago)) Inf-Norm of Grad Fischer Fcn. . 2.8699e-11 eqn: (supply(seattle)) Two-Norm of Grad Fischer Fcn. . 4.0587e-11 FINAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 5.0000e+01 eqn: (supply(san-diego)) Maximum of Grad F . . . . . . . 1.0000e+00 eqn: (supply(seattle)) var: (x(seattle,new-york)) ---- EQU profit zero profit conditions LOWER LEVEL UPPER MARGINAL seattle .new-york -0.225 -0.225 +INF 50.000 seattle .chicago -0.077 -0.077 +INF 300.000 seattle .topeka -0.162 -0.126 +INF . san-diego.new-york -0.225 -0.225 +INF 275.000 san-diego.chicago -0.162 -0.076 +INF . san-diego.topeka -0.126 -0.126 +INF 275.000 ---- EQU supply supply limit at plant i LOWER LEVEL UPPER MARGINAL seattle -350.000 -350.000 +INF . san-diego -600.000 -550.000 +INF . ---- EQU fxdemand fixed demand at market j LOWER LEVEL UPPER MARGINAL new-york 325.000 325.000 +INF 0.225 chicago 300.000 300.000 +INF 0.076 topeka 275.000 275.000 +INF 0.126 ---- VAR w shadow price at supply node i LOWER LEVEL UPPER MARGINAL seattle . . +INF 4.6700E-6 san-diego . . +INF 50.000 ---- VAR p shadow price at demand node j LOWER LEVEL UPPER MARGINAL new-york . 0.225 +INF . chicago . 0.076 +INF . topeka . 0.126 +INF . ---- VAR x shipment quantities in cases LOWER LEVEL UPPER MARGINAL seattle .new-york . 50.000 +INF . seattle .chicago . 300.000 +INF . seattle .topeka . . +INF 0.036 san-diego.new-york . 275.000 +INF . san-diego.chicago . . +INF 0.086 san-diego.topeka . 275.000 +INF . **** REPORT SUMMARY : 0 NONOPT 0 INFEASIBLE 0 UNBOUNDED 0 REDEFINED 0 ERRORS GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 8 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Model Statistics SOLVE equilqty Using MCP From line 106 MODEL STATISTICS BLOCKS OF EQUATIONS 3 SINGLE EQUATIONS 11 BLOCKS OF VARIABLES 3 SINGLE VARIABLES 11 NON ZERO ELEMENTS 27 NON LINEAR N-Z 3 DERIVATIVE POOL 20 CONSTANT POOL 24 CODE LENGTH 28 GENERATION TIME = 0.002 SECONDS 3 MB 24.5.6 r55090 LEX-LEG EXECUTION TIME = 0.002 SECONDS 3 MB 24.5.6 r55090 LEX-LEG GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 9 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) Solution Report SOLVE equilqty Using MCP From line 106 S O L V E S U M M A R Y MODEL equilqty TYPE MCP SOLVER PATH FROM LINE 106 **** SOLVER STATUS 1 Normal Completion **** MODEL STATUS 1 Optimal RESOURCE USAGE, LIMIT 0.006 1000.000 ITERATION COUNT, LIMIT 16 2000000000 EVALUATION ERRORS 0 0 11 row/cols, 27 non-zeros, 22.31% dense. Path 4.7.03 (Fri Nov 27 05:18:03 2015) Written by Todd Munson, Steven Dirkse, and Michael Ferris INITIAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.0000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 3.8922e+02 eqn: (prdemand(chicago)) Maximum of Grad F . . . . . . . 1.0811e+04 eqn: (prdemand(chicago)) var: (p(chicago)) INITIAL JACOBIAN NORM STATISTICS Maximum Row Norm. . . . . . . . 1.0813e+04 eqn: (prdemand(chicago)) Minimum Row Norm. . . . . . . . 2.0000e+00 eqn: (profit(seattle,new-york)) Maximum Column Norm . . . . . . 1.0813e+04 var: (p(chicago)) Minimum Column Norm . . . . . . 2.0000e+00 var: (x(seattle,new-york)) FINAL STATISTICS Inf-Norm of Complementarity . . 1.0311e-11 eqn: (profit(san-diego,new-york)) Inf-Norm of Normal Map. . . . . 1.1369e-13 eqn: (prdemand(new-york)) Inf-Norm of Minimum Map . . . . 1.1369e-13 eqn: (prdemand(new-york)) Inf-Norm of Fischer Function. . 1.1369e-13 eqn: (prdemand(new-york)) Inf-Norm of Grad Fischer Fcn. . 2.4809e-10 eqn: (prdemand(topeka)) Two-Norm of Grad Fischer Fcn. . 3.4958e-10 FINAL POINT STATISTICS Maximum of X. . . . . . . . . . 3.5000e+02 var: (x(seattle,chicago)) Maximum of F. . . . . . . . . . 9.4056e-02 eqn: (profit(seattle,topeka)) Maximum of Grad F . . . . . . . 4.3651e+03 eqn: (prdemand(topeka)) var: (p(topeka)) ---- EQU profit zero profit conditions LOWER LEVEL UPPER MARGINAL seattle .new-york -0.225 -0.167 +INF . seattle .chicago -0.077 -0.077 +INF 350.000 seattle .topeka -0.162 -0.068 +INF . san-diego.new-york -0.225 -0.225 +INF 325.000 san-diego.chicago -0.162 -0.135 +INF . san-diego.topeka -0.126 -0.126 +INF 275.000 ---- EQU supply supply limit at plant i LOWER LEVEL UPPER MARGINAL seattle -350.000 -350.000 +INF 0.058 san-diego -600.000 -600.000 +INF . ---- EQU prdemand price-responsive demand at market j LOWER LEVEL UPPER MARGINAL new-york . . +INF 0.225 chicago . . +INF 0.135 topeka . . +INF 0.126 ---- VAR w shadow price at supply node i LOWER LEVEL UPPER MARGINAL seattle . 0.058 +INF . san-diego . . +INF . ---- VAR p shadow price at demand node j LOWER LEVEL UPPER MARGINAL new-york . 0.225 +INF . chicago . 0.135 +INF . topeka . 0.126 +INF . ---- VAR x shipment quantities in cases LOWER LEVEL UPPER MARGINAL seattle .new-york . . +INF 0.058 seattle .chicago . 350.000 +INF . seattle .topeka . . +INF 0.094 san-diego.new-york . 325.000 +INF . san-diego.chicago . . +INF 0.027 san-diego.topeka . 275.000 +INF . **** REPORT SUMMARY : 0 NONOPT 0 INFEASIBLE 0 UNBOUNDED 0 REDEFINED 0 ERRORS GAMS 24.5.6 r55090 Released Nov 27, 2015 LEX-LEG x86 64bit/Linux 04/29/16 02:42:37 Page 10 Transportation model as equilibrium problem (TRANSMCP,SEQ=126) E x e c u t i o n ---- 112 PARAMETER report summary report fixed flex fixed CF flex CF seattle .new-york 50.000 50.000 50.000 seattle .chicago 300.000 300.000 300.000 350.000 seattle .price 0.058 san-diego.new-york 275.000 275.000 275.000 325.000 san-diego.topeka 275.000 275.000 275.000 275.000 price .new-york 0.225 0.225 0.225 0.225 price .chicago 0.153 0.153 0.076 0.135 price .topeka 0.126 0.126 0.126 0.126 EXECUTION TIME = 0.002 SECONDS 3 MB 24.5.6 r55090 LEX-LEG USER: Computer Sciences Dept. G151218:1517AO-LNX University of Wisconsin-Madison DC8499 License for teaching and research at degree granting institutions **** FILE SUMMARY Input /var/lib/condor/execute/dir_1900406/MODEL.gms Output /var/lib/condor/execute/dir_1900406/solve.out
The model creation seems have bugs and errors.
The solution to
transmcp.gmsThe entire report: