//Input data for Online Solver at https://www.lutanho.net/plt/lotsize_mcm.html //Data source: "Multi-Module Capacitated Lot-Sizing Problem and its Generalizations with //Two-Echelons and Piecewise Concave Production Costs" //by Kartik Kulkarni and Manish Bansal (2019) (https://optimization-online.org/2019/07/7294/) //page 34/55 Table 3: Computational Results for MCLS with n = 3 and 40 time periods: //(C1, C2, C3)=(860, 1650, 2590), Instance 5, OPT=81779.04 //Instance data is available at https://github.com/Bansal-ORGroup/MCLS-LSPC-Data //All costs multiplied by 100 to get integer values //I u_0 y_0 y_I 40; 0; 0; 0; startup x_min fix var x_max fix var x_max fix var x_max demand y_min fix var y_max 0; 0, 311800, 73, 860, 592400, 73, 1650, 909000, 73, 2590; 443; 0, 0, 5, 9999; 0; 0, 295500, 96, 860, 610500, 96, 1650, 902800, 96, 2590; 552; 0, 0, 5, 9999; 0; 0, 286400, 82, 860, 594400, 82, 1650, 901900, 82, 2590; 460; 0, 0, 5, 9999; 0; 0, 301800, 70, 860, 609800, 70, 1650, 903600, 70, 2590; 450; 0, 0, 5, 9999; 0; 0, 306000, 82, 860, 618300, 82, 1650, 890100, 82, 2590; 418; 0, 0, 5, 9999; 0; 0, 297300, 57, 860, 608800, 57, 1650, 898300, 57, 2590; 433; 0, 0, 5, 9999; 0; 0, 290300, 79, 860, 615800, 79, 1650, 909000, 79, 2590; 479; 0, 0, 5, 9999; 0; 0, 285600, 68, 860, 607600, 68, 1650, 916200, 68, 2590; 508; 0, 0, 5, 9999; 0; 0, 299800, 85, 860, 592300, 85, 1650, 914200, 85, 2590; 469; 0, 0, 5, 9999; 0; 0, 296900, 76, 860, 610200, 76, 1650, 916200, 76, 2590; 499; 0, 0, 5, 9999; 0; 0, 298100, 72, 860, 594600, 72, 1650, 887000, 72, 2590; 565; 0, 0, 5, 9999; 0; 0, 295800, 78, 860, 604000, 78, 1650, 906900, 78, 2590; 414; 0, 0, 5, 9999; 0; 0, 295400, 91, 860, 588700, 91, 1650, 913700, 91, 2590; 598; 0, 0, 5, 9999; 0; 0, 314500, 84, 860, 590400, 84, 1650, 908200, 84, 2590; 419; 0, 0, 5, 9999; 0; 0, 295700, 94, 860, 611100, 94, 1650, 887000, 94, 2590; 438; 0, 0, 5, 9999; 0; 0, 302100, 69, 860, 593400, 69, 1650, 895200, 69, 2590; 429; 0, 0, 5, 9999; 0; 0, 293700, 84, 860, 603700, 84, 1650, 904100, 84, 2590; 506; 0, 0, 5, 9999; 0; 0, 288900, 87, 860, 605000, 87, 1650, 888200, 87, 2590; 587; 0, 0, 5, 9999; 0; 0, 313400, 78, 860, 605200, 78, 1650, 908300, 78, 2590; 512; 0, 0, 5, 9999; 0; 0, 294600,100, 860, 601600,100, 1650, 910200,100, 2590; 520; 0, 0, 5, 9999; 0; 0, 285400, 84, 860, 616300, 84, 1650, 883800, 84, 2590; 518; 0, 0, 5, 9999; 0; 0, 292000, 88, 860, 617000, 88, 1650, 890100, 88, 2590; 412; 0, 0, 5, 9999; 0; 0, 305700, 86, 860, 604200, 86, 1650, 908700, 86, 2590; 475; 0, 0, 5, 9999; 0; 0, 285500, 69, 860, 613000, 69, 1650, 892600, 69, 2590; 406; 0, 0, 5, 9999; 0; 0, 311200, 86, 860, 595100, 86, 1650, 895700, 86, 2590; 578; 0, 0, 5, 9999; 0; 0, 289500, 58, 860, 617400, 58, 1650, 898300, 58, 2590; 506; 0, 0, 5, 9999; 0; 0, 287700, 99, 860, 596400, 99, 1650, 919300, 99, 2590; 426; 0, 0, 5, 9999; 0; 0, 286800, 81, 860, 594400, 81, 1650, 891300, 81, 2590; 411; 0, 0, 5, 9999; 0; 0, 304700, 90, 860, 596600, 90, 1650, 917900, 90, 2590; 443; 0, 0, 5, 9999; 0; 0, 293200, 55, 860, 586000, 55, 1650, 916000, 55, 2590; 426; 0, 0, 5, 9999; 0; 0, 297500, 78, 860, 615300, 78, 1650, 908900, 78, 2590; 445; 0, 0, 5, 9999; 0; 0, 314400, 87, 860, 616900, 87, 1650, 896300, 87, 2590; 422; 0, 0, 5, 9999; 0; 0, 307300, 73, 860, 612300, 73, 1650, 913100, 73, 2590; 407; 0, 0, 5, 9999; 0; 0, 309300, 83, 860, 599100, 83, 1650, 909100, 83, 2590; 542; 0, 0, 5, 9999; 0; 0, 290600, 66, 860, 598700, 66, 1650, 913300, 66, 2590; 497; 0, 0, 5, 9999; 0; 0, 305500, 89, 860, 617300, 89, 1650, 910600, 89, 2590; 441; 0, 0, 5, 9999; 0; 0, 297800, 52, 860, 598500, 52, 1650, 899400, 52, 2590; 573; 0, 0, 5, 9999; 0; 0, 308700, 84, 860, 598800, 84, 1650, 894800, 84, 2590; 425; 0, 0, 5, 9999; 0; 0, 297000, 66, 860, 593700, 66, 1650, 904400, 66, 2590; 482; 0, 0, 5, 9999; 0; 0, 290400, 96, 860, 604300, 96, 1650, 894700, 96, 2590; 513; 0, 0, 5, 9999;