Multi-objective unrelated parallel machine scheduling: a Tabu-enhanced iterated Pareto greedy algorithm

This work proposes a high-performance algorithm for solving the multi-objective unrelated parallel machine scheduling problem. The proposed approach is based on the iterated Pareto greedy (IPG) algorithm but exploits the accessible Tabu list (TL) to enhance its performance. To demonstrate the superi...

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Vydané v:	International journal of production research Ročník 54; číslo 4; s. 1110 - 1121
Hlavní autori:	Lin, Shih-Wei, Ying, Kuo-Ching, Wu, Wen-Jie, Chiang, Yen-I
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Taylor & Francis 16.02.2016 Taylor & Francis LLC
Predmet:	Accessibility Algorithms Benchmarking Greedy algorithms Job shops multi-objective Optimization Pareto optimality Performance measurement Production scheduling Scheduling Tabu-enhanced iterated Pareto greedy algorithm unrelated parallel machine
ISSN:	0020-7543, 1366-588X
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