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|Title:||Solving the feeder bus network design problem by genetic algorithms and ant colony optimization||Authors:||Kuan, S.N.
|Keywords:||Ant colony optimization
|Issue Date:||Jun-2006||Citation:||Kuan, S.N., Ong, H.L., Ng, K.M. (2006-06). Solving the feeder bus network design problem by genetic algorithms and ant colony optimization. Advances in Engineering Software 37 (6) : 351-359. ScholarBank@NUS Repository. https://doi.org/10.1016/j.advengsoft.2005.10.003||Abstract:||This paper proposes the design and analysis of two metaheuristics, genetic algorithms and ant colony optimization, for solving the feeder bus network design problem. A study of how these proposed heuristics perform is carried out on several randomly generated test problems to evaluate their computational efficiency and the quality of solutions obtained by them. The results are also compared to those published in the literature. Computational experiments have shown that both heuristics are comparable to the state-of-the-art algorithms such as simulated annealing and tabu search. © 2005 Elsevier Ltd. All rights reserved.||Source Title:||Advances in Engineering Software||URI:||http://scholarbank.nus.edu.sg/handle/10635/63327||ISSN:||09659978||DOI:||10.1016/j.advengsoft.2005.10.003|
|Appears in Collections:||Staff Publications|
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