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Comparison between MOEA/D and NSGA-II on the multi-objective travelling salesman problem

Peng, W and Zhang, Q and Li, H (2009) 'Comparison between MOEA/D and NSGA-II on the multi-objective travelling salesman problem.' Studies in Computational Intelligence, 171. 309 - 324. ISSN 1860-949X

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Most multiobjective evolutionary algorithms are based on Pareto dominance for measuring the quality of solutions during their search, among them NSGA-II is well-known. A very few algorithms are based on decomposition and implicitly or explicitly try to optimize aggregations of the objectives. MOEA/D is a very recent such an algorithm. One of the major advantages of MOEA/D is that it is very easy to design local search operator within it using well-developed single-objective optimization algorithms. This chapter compares the performance of MOEA/D and NSGA-II on the multiobjective travelling salesman problem and studies the effect of local search on the performance of MOEA/D. © 2009 Springer-Verlag Berlin Heidelberg.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 15 Aug 2012 14:50
Last Modified: 30 Jan 2019 16:16

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