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Meta-Heuristics: Advances and Trends in Local Search Paradigms for OptimizationFrom Brand: Springer
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Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.
- Brand: Brand: Springer
- Published on: 1998-11-30
- Released on: 1998-11-30
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.19" w x 6.10" l, 1.61 pounds
- Binding: Paperback
- 511 pages
- Used Book in Good Condition
Most helpful customer reviews
4 of 4 people found the following review helpful.
Decision Support
By A Customer
Once one has read the articles in this book it becomes clear that meta-heuristics are intelligently designed methods to provide decision makers with tools for decision support. Each chapter is self-contained and provides different insights into specific methods (especially genetic algorithms, neural networks, tabu search, simulated annealing). These methods are well explored and explained by means of theoretical as well as practical results, e.g., for vehicle routing or mail delivery or generalized assignment. Ideas on how to implement the methods are also provided. Most papers are easy to read with only some preliminaries in mathematics (or combinatorial optimization). The chapters are carefully collected and could have been accepted for high-quality journals as well. Well done.
0 of 20 people found the following review helpful.
this book must be good@
By A Customer
i have no idea what it is avbout, but it looks really cool from the name and totally confusing nature of it.
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