Meta-Heuristics: Theory and ApplicationsIbrahim H. Osman, James P. Kelly Meta-heuristics have developed dramatically since their inception in the early 1980s. They have had widespread success in attacking a variety of practical and difficult combinatorial optimization problems. These families of approaches include, but are not limited to greedy random adaptive search procedures, genetic algorithms, problem-space search, neural networks, simulated annealing, tabu search, threshold algorithms, and their hybrids. They incorporate concepts based on biological evolution, intelligent problem solving, mathematical and physical sciences, nervous systems, and statistical mechanics. Since the 1980s, a great deal of effort has been invested in the field of combinatorial optimization theory in which heuristic algorithms have become an important area of research and applications. This volume is drawn from the first conference on Meta-Heuristics and contains 41 papers on the state-of-the-art in heuristic theory and applications. The book treats the following meta-heuristics and applications: Genetic Algorithms, Simulated Annealing, Tabu Search, Networks & Graphs, Scheduling and Control, TSP, and Vehicle Routing Problems. It represents research from the fields of Operations Research, Management Science, Artificial Intelligence and Computer Science. |
Contents
22 | |
Zbigniew Michalewicz Evolutionary Computation and Heuristics | 37 |
Heinz Mühlenbein and HansMichael Voigt Gene Pool | 53 |
Mutsunori Yagiura and Toshihide Ibaraki Genetic and Local | 63 |
Geoff Craig Mohan Krishnamoorthy and M Palaniswami | 83 |
Rafael Martí An Aggressive Search Procedure for the Bipartite | 97 |
Yazid M Sharaiha and Richard Thaiss Guided Search for | 114 |
H Abada and E ElDarzi A Metaheuristic for the Timetabling | 133 |
Roberto Battiti Giampietro Tecchiolli and Paolo Tonella Vector | 331 |
Mauro DellAmico and Francesco Maffioli A New Tabu Search | 360 |
Kathryn A Dowsland Simple Tabu Thresholding and the Pallet | 379 |
Fred Glover and Gary A Kochenberger Critical Event Tabu | 406 |
Fred Glover John M Mulvey and Kjetil Hoyland Solving | 429 |
S Hanafi A Freville and A El Abdellaoui Comparison | 449 |
Arne Løkketangen and Fred Glover Probabilistic Move Selection | 466 |
Lutz Sondergeld and Stefan Voß A StarShaped Diversification | 489 |
Peter Brucker and Johann Hurink Complex Sequencing | 150 |
Mauro DellAmico Silvano Martello and Daniele Vigo Heuristic | 167 |
Gregor P Henze Manuel Laguna and Moncef Krarti Heuristics | 183 |
Helmut E Mausser and Stephen R Lawrence Exploiting Block | 203 |
Helena Ramalhinho Lourenço and Michiel Zwijnenburg | 218 |
Takeshi Yamada and Ryohei Nakano JobShop Scheduling | 237 |
Mark A Fleischer Sheldon H Jacobson Cybernetic | 249 |
JeanLuc Lutton and Emmanuelle Philippart A Simulated | 265 |
Norman M Sadeh and Sam R Thangiah Learning to Recognize | 277 |
Mike B Wright and Richard C Marett A Preliminary | 298 |
Ahmed S AlMahmeed Tabu Search Combination | 319 |
Michel Toulouse Teodor G Crainic and Michel Gendreau | 503 |
Fan T Tseng A Study on Algorithms for Selecting r Best | 523 |
Vicente Valls M Ángeles Pérez M Sacramento Quintanilla | 536 |
David L Woodruff Chunking Applied to Reactive Tabu Search | 555 |
Martin Zachariasen and Martin Dam Tabu Search on | 570 |
TRAVELING SALESMAN PROBLEMS | 587 |
JeanYves Potvin and François Guertin The Clustered Traveling | 619 |
Richard W Eglese and Leon Y O Li A Tabu Search Based | 633 |
César Rego and Catherine Roucairol A Parallel Tabu Search | 661 |
Paolo Toth and Daniele Vigo Fast Local Search Algorithms | 677 |
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Common terms and phrases
applied average block boxes candidate list chunking colour combinatorial optimization computational results considered constraints convergence criterion crossover current solution defined distribution edges elements feasible solution Figure frequency genetic algorithm given global Glover graph greedy heuristic implementation improving phase infeasible initial solution instances integer knapsack problem large-step optimization local minima local optima local search memory metaheuristics minimal minimum mixed phase move neighborhood nodes NP-hard number of iterations objective function objective function value Operations Research optimal solution optimum ORSA Journal Osman paper parallel parameter partition penalty performance population probabilistic random randomly restart scheduling problem search algorithm search methods search procedure search threads selection sequence shortest path simulated annealing solution space solving Step structure subsets t₁ Table tabu list tabu search tabu thresholding techniques temperature tion transition traveling salesman problem variable vector Vehicle Routing Problem vertex vertices