Metaheuristics (eBook)
XIV, 410 Seiten
Springer US (Verlag)
978-0-387-71921-4 (ISBN)
This book's aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.
The aim of Metaheuristics: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.
Chapter 1 EXPERIMENTS USING SCATTER SEARCH FOR THE MULTIDEMAND MULTIDIMENSIONAL KNAPSACK PROBLEM 15
Chapter 2 A SCATTER SEARCH HEURISTIC FOR THE FIXED-CHARGE CAPACITATED NETWORK DESIGN PROBLEM 37
Chapter 3 TABU SEARCH-BASED METAHEURISTIC ALGORITHM FOR LARGE-SCALESET COVERING PROBLEMS 54
Chapter 4 LOG- TRUCK SCHEDULING WITH A TABU SEARCH STRATEGY 75
Chapter 5 SOLVING THE CAPACITATEDMULTI-FACILITY WEBER PROBLEM BY SIMULATED ANNEALING, THRESHOLD ACCEPTING AND GENETIC ALGORITHMS 100
Chapter 6 REVIEWER ASSIGNMENT FORCIENTIFIC ARTICLES USINGEMETIC ALGORITHMS 122
Chapter 7 GRASP WITH PATH-RELINKING FOR THE TSP 145
Chapter 8 USING A RANDOMISED ITERATIVE IMPROVEMENT ALGORITHM WITH COMPOSITE NEIGHBOURHOOD STRUCTURES FOR THE UNIVERSITY COURSE TIMETABLING PROBLEM 161
Chapter 9 VARIABLE NEIGHBORHOOD SEARCH FOR THE PROBABILISTIC SATISFIABILITY PROBLEM 179
Chapter 10 THE ACO/F-RACE ALGORITHM FOR COMBINATORIAL OPTIMIZATION UNDER UNCERTAINTY 195
Chapter 11 ADAPTIVE CONTROL OF GENETIC PARAMETERS FOR DYNAMIC COMBINATORIAL PROBLEMS 210
Chapter 12 A MEMETIC ALGORITHM FOR DYNAMIC LOCATION PROBLEMS 229
Chapter 13 A STUDY OF CANONICAL GAs FOR NSOPs 249
Chapter 14 PARTICLE SWARM OPTIMIZATION AND SEQUENTIAL SAMPLING IN NOISY ENVIRONMENTS 265
Chapter 15 EMBEDDING A CHAINED LIN-KERNIGHAN ALGORITHM INTO A DISTRIBUTED ALGORITHM 279
Chapter 16 EXPLORING GRID IMPLEMENTATIONS OF PARALLEL COOPERATIVE METAHEURISTICS 298
Chapter 17 USING EXPERIMENTAL DESIGN TO ANALYZE STOCHASTIC LOCAL SEARCH ALGORITHMS FOR MULTIOBJECTIVE PROBLEMS 325
Chapter 18 DISTANCE MEASURES AND FITNESS-DISTANCE ANALYSIS FOR THE CAPACITATED VEHICLE ROUTING PROBLEM 345
Chapter 19 TUNING TABU SEARCH STRATEGIES VIA VISUAL DIAGNOSIS 365
Chapter 20 SOLVING VEHICLE ROUTING USING IOPT 389
| Erscheint lt. Verlag | 13.8.2007 |
|---|---|
| Reihe/Serie | Operations Research/Computer Science Interfaces Series | Operations Research/Computer Science Interfaces Series |
| Zusatzinfo | XIV, 410 p. 66 illus. |
| Verlagsort | New York |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Technik | |
| Wirtschaft ► Allgemeines / Lexika | |
| Wirtschaft ► Betriebswirtschaft / Management ► Planung / Organisation | |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| Wirtschaft ► Volkswirtschaftslehre | |
| Schlagworte | algorithm • algorithms • Analysis • combinatorial optimization • Complex Systems • Data Mining • Genetic algorithms • Metaheuristic • Optimization • programming • Scheduling • Tools • Variable |
| ISBN-10 | 0-387-71921-0 / 0387719210 |
| ISBN-13 | 978-0-387-71921-4 / 9780387719214 |
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