Sustainable Process Plan Generation in RMS: A Comparative Study of Two Multi-objective Evolutionary Approaches - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems Access content directly
Conference Papers Year : 2021

Sustainable Process Plan Generation in RMS: A Comparative Study of Two Multi-objective Evolutionary Approaches

Abstract

In today’s manufacturing industry, staying competitive requires being both cost and time effective, as well as being environmentally benign. In this paper, two versions of the well-known non-dominated sorting genetic algorithm (NSGA) namely Dynamic-NSGA-II and NSGA-III are proposed and compared to solve an environmental oriented multi-objective single unit process plan generation problem in a reconfigurable manufacturing environment. In addition to the traditional total production cost and total production time, two other criteria namely, total amount of hazardous liquid waste and total amount of greenhouse gases (GHG) emitted are minimized. Firstly, a non-linear multi-objective integer program (NL-MOIP) is proposed. Secondly, to illustrate the efficiency of the two approaches, several instances of the problem are experimented and the obtained results are analyzed using three metrics respectively spacing metric, inverted generational distance and cardinality of the mixed Pareto fronts.
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hal-03526660 , version 1 (14-01-2022)

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Imen Khettabi, Lyes Benyoucef, Mohamed Amine Boutiche. Sustainable Process Plan Generation in RMS: A Comparative Study of Two Multi-objective Evolutionary Approaches. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.329-339, ⟨10.1007/978-3-030-85906-0_37⟩. ⟨hal-03526660⟩
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