Soumen Atta1, Priya Ranjan Sinha Mahapatra2, Anirban Mukhopadhyay2
1Laboratoire des Sciences du Numérique de Nantes (LS2N), UMR 6004, UFR Sciences et Techniques, Université de Nantes, IMT Atlantique, 4 Rue Alfred
Kastler, Nantes 44307, France
2Department of Computer Science and Engineering, University of Kalyani, Kalyani-741235, West Bengal, India
Email addresses: soumen.atta@univ-nantes.fr;soumen.atta@ls2n.fr;priya@klyuniv.ac.in;anirban@klyuniv.ac.in
The instances for the fuzzy capacitated maximal covering location problem (FCMCLP) mentioned in this page are generated using the maximal covering location problem (MCLP) [1, 2] instances which are available at http://www.lac.inpe.br/~lorena/instancias.html. We have created 84 FCMCLP instances. The size of an instance is determined by the number of customers (m). Each instance of FCMCLP consists of degree of coverage matrix having size m × m, demand vector of size m × 1, and supply capacity vector having size m × 1. The obtained best solution for each of these 84 instances are shown in the following table.
Cite as: Soumen Atta, Priya Ranjan SinhaMahapatra, AnirbanMukhopadhyay. Solving a new variant of capacitated maximal covering location problem with fuzzy coverage area using metaheuristic approaches. Computers & Industrial Engineering, Elsevier, Vol. 170, Article 108315, 2022.
Click here to download all the instances as single zip file.
| m | k | Open facility set | Cov% |
| 324 | 1 | 32 | 37.03 |
| 324 | 2 | 156 21 | 65.14 |
| 324 | 3 | 156 58 262 | 86.24 |
| 324 | 4 | 156 45 294 20 | 93.29 |
| 324 | 5 | 258 32 234 68 152 | 98.82 |
| 324 | 6 | 105 22 324 127 195 281 | 99.78 |
| 324 | 7 | 191 109 264 25 129 45 229 or, 105 168 274 211 133 28 45 |
100 |
| 402 | 1 | 11 | 28.15 |
| 402 | 2 | 39 396 | 56.10 |
| 402 | 3 | 179 44 159 | 77.25 |
| 402 | 4 | 21 44 160 339 | 91.78 |
| 402 | 5 | 385 21 141 263 93 | 96.83 |
| 402 | 6 | 13 383 158 263 184 297 | 99.32 |
| 402 | 7 | 3 385 109 263 189 293 136 | 99.93 |
| 402 | 8 | 27 383 189 303 63 117 149 263 | 100 |
| 402 | 9 | 20 383 105 351 182 122 137 253 1 or, 193 383 167 335 68 217 114 259 37 |
100 |
| 500 | 1 | 492 | 22.83 |
| 500 | 2 | 20 469 | 45.67 |
| 500 | 3 | 84 457 488 | 66.44 |
| 500 | 4 | 149 465 76 472 | 79.94 |
| 500 | 5 | 65 423 37 472 294 or, 37 423 65 473 294 |
88.58 |
| 500 | 6 | 20 391 90 500 294 358 | 92.83 |
| 500 | 7 | 122 231 19 88 360 390 500 | 95.80 |
| 500 | 8 | 9 440 204 127 231 350 88 401 | 98.24 |
| 500 | 9 | 477 10 133 89 154 451 351 298 390 | 99.26 |
| 500 | 10 | 20 430 99 196 304 321 468 387 218 117 | 99.72 |
| 500 | 11 | 56 390 100 165 261 435 428 321 242 122 477 | 99.85 |
| 500 | 12 | 11 390 87 274 309 333 246 315 130 154 40 477 | 99.98 |
| 500 | 13 | 477 429 99 268 242 285 390 368 201 10 128 356 58 or, 39 498 318 277 425 242 348 390 153 33 117 102 166 |
100 |
| 708 | 1 | 11 | 18.60 |
| 708 | 2 | 21 608 | 37.20 |
| 708 | 3 | 32 639 656 | 55.80 |
| 708 | 4 | 95 639 31 649 | 70.70 |
| 708 | 5 | 21 639 162 370 649 | 81.33 |
| 708 | 6 | 22 553 95 370 662 443 | 86.05 |
| 708 | 7 | 22 599 95 375 242 394 553 | 88.97 |
| 708 | 8 | 23 608 163 370 62 396 549 689 | 92.13 |
| 708 | 9 | 22 609 163 285 72 313 592 694 399 | 94.48 |
| 708 | 10 | 24 554 124 285 174 396 490 689 611 152 | 97.20 |
| 708 | 11 | 36 559 128 285 174 435 490 689 71 152 515 | 97.83 |
| 708 | 12 | 24 554 124 285 654 429 490 689 601 152 515 188 | 98.35 |
| 708 | 13 | 3 559 100 295 662 399 490 689 420 137 516 239 318 | 99.34 |
| 708 | 14 | 56 559 106 295 661 399 490 689 420 171 516 239 328 26 | 99.59 |
| 708 | 15 | 65 553 106 296 652 444 512 689 478 171 540 237 328 26 658 | 99.86 |
| 818 | 1 | 11 | 15.43 |
| 818 | 2 | 21 648 | 30.86 |
| 818 | 3 | 32 679 696 | 46.28 |
| 818 | 4 | 32 679 809 696 | 59.97 |
| 818 | 5 | 173 681 809 79 689 | 72.00 |
| 818 | 6 | 21 679 809 160 366 689 | 81.00 |
| 818 | 7 | 21 679 809 160 366 689 415 | 85.61 |
| 818 | 8 | 22 594 809 160 366 703 415 482 | 89.05 |
| 818 | 9 | 22 639 809 160 366 238 415 447 593 | 92.15 |
| 818 | 10 | 73 44 782 160 362 237 415 295 594 450 | 93.35 |
| 818 | 11 | 21 641 782 156 328 301 415 247 593 451 702 | 94.82 |
| 818 | 12 | 12 649 761 161 316 247 417 452 667 618 72 783 | 95.98 |
| 818 | 13 | 22 662 809 156 327 290 415 615 580 492 238 808 626 | 97.11 |
| 818 | 14 | 11 593 809 156 318 175 415 485 551 640 686 793 555 281 | 98.80 |
| 818 | 15 | 11 593 809 146 361 184 415 485 551 640 686 793 555 296 92 | 99.57 | 700 | 1 | 94 | 17.01 | 700 | 2 | 28 583 | 34.02 | 700 | 3 | 2 642 471 | 51.03 | 700 | 4 | 14 493 397 270 | 68.04 | 700 | 5 | 399 156 512 451 561 | 83.36 | 700 | 6 | 561 563 14 661 406 451 | 87.44 | 700 | 7 | 634 307 489 14 454 584 406 | 89.54 | 700 | 8 | 236 260 268 451 355 406 661 584 | 91.69 | 700 | 9 | 234 561 584 97 354 296 661 611 697 | 93.21 | 700 | 10 | 634 572 141 561 296 355 563 406 661 657 | 94.07 | 700 | 11 | 15 270 296 355 563 661 582 561 618 212 406 | 94.60 | 700 | 12 | 94 96 112 141 296 355 563 406 661 540 561 665 | 95.36 | 900 | 1 | 11 | 13.18 | 900 | 2 | 60 249 | 26.35 | 900 | 3 | 1 317 855 | 39.53 | 900 | 4 | 40 358 851 190 | 52.70 | 900 | 5 | 7 413 810 167 843 | 65.88 | 900 | 6 | 15 366 893 179 829 421 | 79.05 | 900 | 7 | 11 249 843 194 832 349 133 | 92.22 | 900 | 8 | 350 87 810 778 174 438 133 732 | 97.54 | 900 | 9 | 608 847 882 151 815 451 594 746 545 | 98.29 | 900 | 10 | 473 196 204 217 732 778 722 360 421 737 | 98.24 | 900 | 11 | 6 558 590 324 523 350 121 732 594 747 772 | 98.55 | 900 | 12 | 12 704 133 53 815 558 161 231 438 763 23 114 | 98.84 | 900 | 13 | 278 589 594 388 778 445 746 666 158 16 732 520 866 | 98.86 |
References:
[1] Lorena, L. A., & Pereira, M. A. (2002). A Lagrangean/surrogate heuristic for the maximal covering location problem using Hillman's edition. International Journal of Industrial Engineering, 9, 57-67.
[2] Atta, S., Mahapatra, P. R. S., & Mukhopadhyay, A. (2018). Solving maximal covering location problem using genetic algorithm with local refinement. Soft Computing, 22(12), 3891-3906.
This page is maintained by Dr. Soumen Atta, Ph.D..
This page was created on February 29, 2020.