4.5 Article

Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems

期刊

COMPUTERS & OPERATIONS RESEARCH
卷 38, 期 11, 页码 1521-1533

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2011.01.010

关键词

Scheduling; Flowshop; Multi-objective; Iterated Greedy

资金

  1. Spanish Ministry of Science and Innovation [DPI2008-03511/DPI]
  2. IMPIVA - Institute for the Small and Medium Valencian Enterprise [IMIDIC/2008/137, IMIDIC/2009/198, IMIDIC/2010/175]
  3. Polytechnic University of Valencia [3147]

向作者/读者索取更多资源

Multi-objective optimisation problems have seen a large impulse in the last decades. Many new techniques for solving distinct variants of multi-objective problems have been proposed. Production scheduling, as with other operations management fields, is no different. The flowshop problem is among the most widely studied scheduling settings. Recently, the Iterated Greedy methodology for solving the single-objective version of the flowshop problem has produced state-of-the-art results. This paper proposes a new algorithm based on Iterated Greedy technique for solving the multi-objective permutation flowshop problem. This algorithm is characterised by an effective initialisation of the population, management of the Pareto front, and a specially tailored local search, among other things. The proposed multi-objective Iterated Greedy method is shown to outperform other recent approaches in comprehensive computational and statistical tests that comprise a large number of instances with objectives involving makespan, tardiness and flowtime. Lastly, we use a novel graphical tool to compare the performances of stochastic Pareto fronts based on Empirical Attainment Functions. (C) 2011 Elsevier Ltd. All rights reserved.

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