%0 Conference Proceedings
%T Evolutionary Multi-objective Optimization of Business Process Designs with MA-NSGAII
%+ Laboratoire de Recherche en Informatique [ESI-SBA, Sidi Bel Abbès] (LabRI-SBA)
%+ Université d'Oran 1 Ahmed Ben Bella [Oran]
%A Mahammed, Nadir
%A Benslimane, Sidi, Mohamed
%A Hamdani, Nesrine
%Z Part 4: Optimization
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th IFIP International Conference on Computational Intelligence and Its Applications (CIIA)
%C Oran, Algeria
%Y Abdelmalek Amine
%Y Malek Mouhoub
%Y Otmane Ait Mohamed
%Y Bachir Djebbar
%I Springer International Publishing
%3 Computational Intelligence and Its Applications
%V AICT-522
%P 341-351
%8 2018-05-08
%D 2018
%R 10.1007/978-3-319-89743-1_30
%K Multi-objective optimization
%K Evolutionary computing
%K Genetic algorithm
%K Selection operator
%K Business process
%Z Computer Science [cs]Conference papers
%X Optimization is known as the process of finding the best possible solution to a problem given a set of constraints. The problem becomes challenging when dealing with conflicting objectives, which leads to a multiplicity of solutions. Evolutionary algorithms, which use a population approach in their search procedures, are advised to suitably solve the problem. In this article, we present an approach for an evolutionary combinatorial multi-objective optimization of business process designs using a variation of NSGAII, baptized MA-NSGAII. The variants of NSGAII are numerous. In fact, the vast majority deals either with the crossover operator or with the crowding distance. We discuss an optimization Framework that uses (i) a proposal of effective Fitness function, (ii) 02 contradictory criteria to optimize and (iii) an original selection technique. We test the proposed Framework with a real life case of multi-objective optimization of business process designs. The obtained results clearly indicate that an effectual Fitness function combined with the appropriate selection operator affects undeniably quality and quantity of solutions.
%G English
%Z TC 5
%2 https://inria.hal.science/hal-01913899/document
%2 https://inria.hal.science/hal-01913899/file/467079_1_En_30_Chapter.pdf
%L hal-01913899
%U https://inria.hal.science/hal-01913899
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-CIIA
%~ IFIP-AICT-522