Overview
- Discusses how CS can be adapted to solve combinatorial optimization problems, from their discretization to the pseudocode
- Presents adaptation as a model for other metaheuristics
- Offers essential support to help beginning researchers understand how the same metaheuristic works in a search space for different combinatorial optimization problems
Part of the book series: Springer Tracts in Nature-Inspired Computing (STNIC)
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Table of contents (6 chapters)
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Theory and Formulations
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Application
Keywords
About this book
This book provides a literature review of techniques used to pass from continuous to combinatorial space, before discussing a detailed example with individual steps of how cuckoo search (CS) can be adapted to solve combinatorial optimization problems. It demonstrates the application of CS to three different problems and describes their source code. The content is divided into five chapters, the first of which provides a technical description, together with examples of combinatorial search spaces. The second chapter summarizes a diverse range of methods used to solve combinatorial optimization problems. In turn, the third chapter presents a description of CS, its formulation and characteristics. In the fourth chapter, the application of discrete cuckoo search (DCS) to solve three POCs (the traveling salesman problem, quadratic assignment problem and job shop scheduling problem) is explained, focusing mainly on a reinterpretation of the terminology used in CS and its source of inspiration. In closing, the fifth chapter discusses random-key cuckoo search (RKCS) using random keys to represent positions found by cuckoo search in the TSP and QAP solution space.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Discrete Cuckoo Search for Combinatorial Optimization
Authors: Aziz Ouaarab
Series Title: Springer Tracts in Nature-Inspired Computing
DOI: https://doi.org/10.1007/978-981-15-3836-0
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-3835-3Published: 25 March 2020
Softcover ISBN: 978-981-15-3838-4Published: 25 March 2021
eBook ISBN: 978-981-15-3836-0Published: 24 March 2020
Series ISSN: 2524-552X
Series E-ISSN: 2524-5538
Edition Number: 1
Number of Pages: XV, 130
Number of Illustrations: 29 b/w illustrations
Topics: Computational Intelligence, Discrete Optimization, Algorithm Analysis and Problem Complexity, Algorithms