Sustainable Process Plan Generation in RMS: A Comparative Study of Two Multi-objective Evolutionary Approaches - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

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

Résumé

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.
Fichier principal
Vignette du fichier
520759_1_En_37_Chapter.pdf (446.64 Ko) Télécharger le fichier
Origine : Accord explicite pour ce dépôt
Licence : CC BY - Paternité

Dates et versions

hal-03526660 , version 1 (14-01-2022)

Licence

Paternité

Identifiants

Citer

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⟩
27 Consultations
8 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More