Local Search in Combinatorial OptimizationEmile Aarts, Jan Karel Lenstra In the past three decades, local search has grown from a simple heuristic idea into a mature field of research in combinatorial optimization that is attracting ever-increasing attention. Local search is still the method of choice for NP-hard problems as it provides a robust approach for obtaining high-quality solutions to problems of a realistic size in reasonable time. Local Search in Combinatorial Optimization covers local search and its variants from both a theoretical and practical point of view, each topic discussed by a leading authority. This book is an important reference and invaluable source of inspiration for students and researchers in discrete mathematics, computer science, operations research, industrial engineering, and management science. |
Contents
1 | |
2 Computational complexity Mihalis Yannakak | 19 |
3 Local improvement on discrete structures Craig A Tovey | 57 |
4 Simulated annealing Emile H L Aarts Jan H M Korst Peter J M van Laarhoven | 91 |
5 Tabu search Alain Hertz Eric Taillard Dominique de Werra | 121 |
6 Genetic algorithms Heinz Mühlenbein | 137 |
7 Artificial neural networks Carsten Peterson Bo Söderberg | 173 |
a case study David S Johnson Lyle A McGeoch | 215 |
handling edge exchanges Gerard A P Kindervater Martin W P Savelsbergh | 337 |
11 Machine scheduling Edward J Anderson Celia A Glass Chris N Potts | 361 |
12 VLSI layout synthesis Emile H L Aarts Peter J M van Laarhoven C L Liu Peichen Pan | 415 |
13 Code design Iiro S Honkala Patric R J Östergċrd | 441 |
457 | |
Author index | 495 |
507 | |
modern heuristics Michel Gendreau Gilbert Laporte JeanYves Potvin | 311 |