@inbook{5ee650d4a5b947989a163ed89a3834d9,
title = "Comparison between MOEA/D and NSGA-II on the multi-objective travelling salesman problem",
abstract = "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.",
author = "Wei Peng and Qingfu Zhang and Hui Li",
year = "2009",
doi = "10.1007/978-3-540-88051-6\_14",
language = "英语",
isbn = "9783540880509",
series = "Studies in Computational Intelligence",
pages = "309--324",
editor = "Chi-Keong Goh and Tan, \{Kay Chen\} and Yew-Soon Ong",
booktitle = "Multi-Objective Memetic Algorithms",
}