%0 Conference Paper
%F Oral 
%T Sustainable Process Plan Generation in RMS: A Comparative Study of Two Multi-objective Evolutionary Approaches
%+ Université des Sciences et de la Technologie Houari Boumediene = University of Sciences and Technology Houari Boumediene [Alger] (USTHB)
%+ Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon) (LIS)
%A Khettabi, Imen
%A Benyoucef, Lyes
%A Boutiche, Mohamed Amine
%< avec comité de lecture
%3 IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Nantes, France
%Y Alexandre Dolgui
%Y Alain Bernard
%Y Gregor von Cieminski
%Y David Romero
%I Springer International Publishing
%C Cham
%S Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
%V AICT-632
%P 329-339
%8 2021-09-05
%D 2021
%R 10.1007/978-3-030-85906-0_37
%Z Computer Science [cs]
%Z Computer Science [cs]/Operations Research [math.OC]Conference papers
%X 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.
%G English
%Z TC5
%Z WG 5,7
%2 https://hal.science/hal-03526660/document
%2 https://hal.science/hal-03526660/file/520759_1_En_37_Chapter.pdf
%L hal-03526660
%U https://hal.science/hal-03526660
%~ UNIV-TLN
%~ CNRS
%~ UNIV-AMU
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ TDS-MACS
%~ IFIP-APMS
%~ IFIP-WG5-7
%~ IFIP-TCS
%~ LIS-LAB
%~ INCIAM
%~ IFIP-AICT-632