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Genetic algorithms-baes solution approach to combinatorial optimisation problems

Genetic algorithms-baes solution approach to combinatorial optimisation problems This paper presents various methods and algorithms used in the solution of combinatorial optimisation problems. A definition of a combinatorial optimisation problem is first given. The definition is followed by a discussion on the depth first branch-and-bound algorithm and the local search algorithm; two approaches used for solving these kinds of problems. An introduction to Genetic Algorithms (GAs) coupled with an explanation of their role in solving combinatorial optimisation problems such as the travelling salesman problem is then presented. The discussion on genetic algorithms focuses on the advantages and disadvantages of using this technique as a tool or solving combinatorial optimisation problems. A sample instance of the Travelling Salesman Problem (TSP) is then solved using a GA. Finally, some conclusions are presented to emphasise the implications, benefits and drawbacks of using genetic algorithms in the solution of various combinatorial optimisation problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Knowledge Management Studies Inderscience Publishers

Genetic algorithms-baes solution approach to combinatorial optimisation problems

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1743-8268
eISSN
1743-8276
DOI
10.1504/IJKMS.2008.019754
Publisher site
See Article on Publisher Site

Abstract

This paper presents various methods and algorithms used in the solution of combinatorial optimisation problems. A definition of a combinatorial optimisation problem is first given. The definition is followed by a discussion on the depth first branch-and-bound algorithm and the local search algorithm; two approaches used for solving these kinds of problems. An introduction to Genetic Algorithms (GAs) coupled with an explanation of their role in solving combinatorial optimisation problems such as the travelling salesman problem is then presented. The discussion on genetic algorithms focuses on the advantages and disadvantages of using this technique as a tool or solving combinatorial optimisation problems. A sample instance of the Travelling Salesman Problem (TSP) is then solved using a GA. Finally, some conclusions are presented to emphasise the implications, benefits and drawbacks of using genetic algorithms in the solution of various combinatorial optimisation problems.

Journal

International Journal of Knowledge Management StudiesInderscience Publishers

Published: Jan 1, 2008

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