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Discrete optimization

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417: 95:) or constraint programs, any constraint program can be formulated as an integer program and vice versa, and constraint and integer programs can often be given a combinatorial interpretation. 314: 185: 309: 91:
These branches are all closely intertwined however, since many combinatorial optimization problems can be modeled as integer programs (e.g.
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Hammer, P. L.; Johnson, E. L.; Korte, B. H. (2000), "Conclusive remarks",
867: 249: 155:, Annals of Discrete Mathematics, vol. 5, Elsevier, pp. 427–453 193: 269: 589: 74: 51: 42:
used in a discrete optimization problem are restricted to be
62:
Three notable branches of discrete optimization are:
706: 150: 897: 179: 740: 127:A First Course in Combinatorial Optimization 218: 186: 172: 432: 420:Optimization computes maxima and minima. 504: 898: 824: 640: 616:Principal pivoting algorithm of Lemke 503: 431: 217: 167: 123: 16:Branch of mathematical optimization 13: 825: 415: 260:Successive parabolic interpolation 14: 917: 641: 580:Projective algorithm of Karmarkar 46:—that is, to assume only a 575:Ellipsoid algorithm of Khachiyan 478:Sequential quadratic programming 315:Broyden–Fletcher–Goldfarb–Shanno 533:Reduced gradient (Frank–Wolfe) 144: 117: 69:, which refers to problems on 1: 863:Spiral optimization algorithm 483:Successive linear programming 110: 77:and other discrete structures 601:Simplex algorithm of Dantzig 473:Augmented Lagrangian methods 7: 98: 57: 50:set of values, such as the 10: 922: 67:combinatorial optimization 906:Mathematical optimization 880: 833: 820: 804:Push–relabel maximum flow 779: 695: 653: 649: 636: 606:Revised simplex algorithm 588: 560: 546: 516: 512: 499: 465: 444: 440: 427: 413: 389: 337: 300: 277: 268: 230: 226: 213: 329:Symmetric rank-one (SR1) 310:Berndt–Hall–Hall–Hausman 153:Discrete Optimization II 853:Parallel metaheuristics 661:Approximation algorithm 372:Powell's dog leg method 324:Davidon–Fletcher–Powell 220:Unconstrained nonlinear 36:continuous optimization 838:Evolutionary algorithm 421: 86:constraint programming 611:Criss-cross algorithm 434:Constrained nonlinear 419: 240:Golden-section search 38:, some or all of the 20:Discrete optimization 528:Cutting-plane method 105:Diophantine equation 858:Simulated annealing 676:Integer programming 666:Dynamic programming 506:Convex optimization 367:Levenberg–Marquardt 81:integer programming 28:applied mathematics 538:Subgradient method 422: 347:Conjugate gradient 255:Nelder–Mead method 44:discrete variables 893: 892: 876: 875: 816: 815: 812: 811: 775: 774: 736: 735: 632: 631: 628: 627: 624: 623: 495: 494: 491: 490: 411: 410: 407: 406: 385: 384: 124:Lee, Jon (2004), 913: 822: 821: 738: 737: 704: 703: 681:Branch and bound 671:Greedy algorithm 651: 650: 638: 637: 558: 557: 514: 513: 501: 500: 442: 441: 429: 428: 377:Truncated Newton 292:Wolfe conditions 275: 274: 228: 227: 215: 214: 188: 181: 174: 165: 164: 158: 156: 148: 142: 140: 121: 34:. As opposed to 32:computer science 921: 920: 916: 915: 914: 912: 911: 910: 896: 895: 894: 889: 872: 829: 808: 771: 732: 709: 698: 691: 645: 620: 584: 551: 542: 519: 508: 487: 461: 457:Penalty methods 452:Barrier methods 436: 423: 403: 399:Newton's method 381: 333: 296: 264: 245:Powell's method 222: 209: 192: 162: 161: 149: 145: 138: 122: 118: 113: 101: 60: 22:is a branch of 17: 12: 11: 5: 919: 909: 908: 891: 890: 888: 887: 881: 878: 877: 874: 873: 871: 870: 865: 860: 855: 850: 845: 840: 834: 831: 830: 827:Metaheuristics 818: 817: 814: 813: 810: 809: 807: 806: 801: 799:Ford–Fulkerson 796: 791: 785: 783: 777: 776: 773: 772: 770: 769: 767:Floyd–Warshall 764: 759: 758: 757: 746: 744: 734: 733: 731: 730: 725: 720: 714: 712: 701: 693: 692: 690: 689: 688: 687: 673: 668: 663: 657: 655: 647: 646: 634: 633: 630: 629: 626: 625: 622: 621: 619: 618: 613: 608: 603: 597: 595: 586: 585: 583: 582: 577: 572: 570:Affine scaling 566: 564: 562:Interior point 555: 544: 543: 541: 540: 535: 530: 524: 522: 510: 509: 497: 496: 493: 492: 489: 488: 486: 485: 480: 475: 469: 467: 466:Differentiable 463: 462: 460: 459: 454: 448: 446: 438: 437: 425: 424: 414: 412: 409: 408: 405: 404: 402: 401: 395: 393: 387: 386: 383: 382: 380: 379: 374: 369: 364: 359: 354: 349: 343: 341: 335: 334: 332: 331: 326: 321: 312: 306: 304: 298: 297: 295: 294: 289: 283: 281: 272: 266: 265: 263: 262: 257: 252: 247: 242: 236: 234: 224: 223: 211: 210: 191: 190: 183: 176: 168: 160: 159: 143: 136: 115: 114: 112: 109: 108: 107: 100: 97: 89: 88: 83: 78: 59: 56: 15: 9: 6: 4: 3: 2: 918: 907: 904: 903: 901: 886: 883: 882: 879: 869: 866: 864: 861: 859: 856: 854: 851: 849: 846: 844: 843:Hill climbing 841: 839: 836: 835: 832: 828: 823: 819: 805: 802: 800: 797: 795: 792: 790: 787: 786: 784: 782: 781:Network flows 778: 768: 765: 763: 760: 756: 753: 752: 751: 748: 747: 745: 743: 742:Shortest path 739: 729: 726: 724: 721: 719: 716: 715: 713: 711: 710:spanning tree 705: 702: 700: 694: 686: 682: 679: 678: 677: 674: 672: 669: 667: 664: 662: 659: 658: 656: 652: 648: 644: 643:Combinatorial 639: 635: 617: 614: 612: 609: 607: 604: 602: 599: 598: 596: 594: 591: 587: 581: 578: 576: 573: 571: 568: 567: 565: 563: 559: 556: 554: 549: 545: 539: 536: 534: 531: 529: 526: 525: 523: 521: 515: 511: 507: 502: 498: 484: 481: 479: 476: 474: 471: 470: 468: 464: 458: 455: 453: 450: 449: 447: 443: 439: 435: 430: 426: 418: 400: 397: 396: 394: 392: 388: 378: 375: 373: 370: 368: 365: 363: 360: 358: 355: 353: 350: 348: 345: 344: 342: 340: 339:Other methods 336: 330: 327: 325: 322: 320: 316: 313: 311: 308: 307: 305: 303: 299: 293: 290: 288: 285: 284: 282: 280: 276: 273: 271: 267: 261: 258: 256: 253: 251: 248: 246: 243: 241: 238: 237: 235: 233: 229: 225: 221: 216: 212: 208: 204: 200: 196: 189: 184: 182: 177: 175: 170: 169: 166: 154: 147: 139: 137:9780521010122 133: 129: 128: 120: 116: 106: 103: 102: 96: 94: 93:shortest path 87: 84: 82: 79: 76: 72: 68: 65: 64: 63: 55: 53: 49: 45: 41: 37: 33: 29: 25: 21: 848:Local search 794:Edmonds–Karp 750:Bellman–Ford 520:minimization 352:Gauss–Newton 302:Quasi–Newton 287:Trust region 195:Optimization 152: 146: 126: 119: 90: 61: 24:optimization 19: 18: 868:Tabu search 279:Convergence 250:Line search 699:algorithms 207:heuristics 199:Algorithms 111:References 654:Paradigms 553:quadratic 270:Gradients 232:Functions 40:variables 900:Category 885:Software 762:Dijkstra 593:exchange 391:Hessians 357:Gradient 99:See also 75:matroids 58:Branches 52:integers 48:discrete 728:Kruskal 718:BorĹŻvka 708:Minimum 445:General 203:methods 590:Basis- 548:Linear 518:Convex 362:Mirror 319:L-BFGS 205:, and 134:  71:graphs 789:Dinic 697:Graph 755:SPFA 723:Prim 317:and 132:ISBN 30:and 685:cut 550:and 26:in 902:: 201:, 197:: 73:, 54:. 683:/ 187:e 180:t 173:v 157:. 141:.

Index

optimization
applied mathematics
computer science
continuous optimization
variables
discrete variables
discrete
integers
combinatorial optimization
graphs
matroids
integer programming
constraint programming
shortest path
Diophantine equation
A First Course in Combinatorial Optimization
ISBN
9780521010122
v
t
e
Optimization
Algorithms
methods
heuristics
Unconstrained nonlinear
Functions
Golden-section search
Powell's method
Line search

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