Details
Discrete Cuckoo Search for Combinatorial Optimization
Springer Tracts in Nature-Inspired Computing
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 24.03.2020 |
| ISBN/EAN: | 9789811538360 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
<p>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.<br></p><br>
Combinatorial optimization space.- Solving COPs.- From CS to DCS.- DCS and the studied COPs.- Cuckoo search Random key encoding.
Dr. Aziz Ouaarab is an Assistant Professor of Computer Sciences and Applied Mathematics at Cadi Ayyad University of Marrakech, Morocco. Dr. Ouaarab received his M.S. degree in 2011 and his D.Phil. in Engineering Sciences in 2015, both from Mohammed V University of Rabat, Morocco. His thesis project focused on the use of nature-inspired metaheuristics to solve combinatorial optimization problems, and on cuckoo search as a special case to be improved. He joined the Computer Engineering and Systems Laboratory at the Faculty of Sciences and Techniques, Marrakech, in 2019. His research chiefly focuses on combinatorial optimization problems and how they can be solved by means of swarm intelligence and nature-inspired metaheuristics. Dr. Ouaarab currently serves on the editorial board of the International Journal of Bio-Inspired Computation.
<p>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.<br></p><br>
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
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