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Mathematics | Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity

Bioinspired Computation in Combinatorial Optimization

Algorithms and Their Computational Complexity

Neumann, Frank, Witt, Carsten

2010, XII, 216 p.

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  • Provides a comprehensive introduction for researchers
  • Written by authors who have given tutorials on this topic at major international conferences
  • Features text that has been class-tested by the authors and their collaborators

Bioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these search heuristics. This is the first book to explain the most important results achieved in this area.

The authors show how runtime behavior can be analyzed in a rigorous way. in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems. Classical single-objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help to speed up bioinspired computation for single-objective optimization problems.

This book will be valuable for graduate and advanced undergraduate courses on bioinspired computation, as it offers clear assessments of the benefits and drawbacks of various methods. It offers a self-contained presentation, theoretical foundations of the techniques, a unified framework for analysis, and explanations of common proof techniques, so it can also be used as a reference for researchers in the areas of natural computing, optimization and computational complexity.

 

Content Level » Research

Keywords » Bioinspired computing - Computational complexity - Evolutionary algorithms - Minimum spanning trees - Multiobjective optimization - Natural computing - Optimization - algorithms - combinatorial optimization - evolutionary algorithm - multi-objective optimization - scheduling

Related subjects » Artificial Intelligence - Mathematics - Software Engineering - Theoretical Computer Science

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