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

Minella, G., Ruiz, R., Ciavotta, M. (2011). Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems. COMPUTERS & OPERATIONS RESEARCH, 38(11), 1521-1533 [10.1016/j.cor.2011.01.010].

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

Ciavotta, M
2011

Abstract

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
Articolo in rivista - Articolo scientifico
Scheduling; Flowshop; Multi-objective Iterated Greedy
English
1521
1533
13
Minella, G., Ruiz, R., Ciavotta, M. (2011). Restarted Iterated Pareto Greedy algorithm for multi-objective flowshop scheduling problems. COMPUTERS & OPERATIONS RESEARCH, 38(11), 1521-1533 [10.1016/j.cor.2011.01.010].
Minella, G; Ruiz, R; Ciavotta, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/186547
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