%0 Conference Proceedings
%T A New Hybrid Genetic Algorithm to Deal with the Flow Shop Scheduling Problem for Makespan Minimization
%+ Université Aboubekr Belkaid - University of Belkaïd Abou Bekr [Tlemcen]
%A Boumediene, Fatima, Zohra
%A Houbad, Yamina
%A Hassam, Ahmed
%A Ghomri, Latéfa
%Z Part 5: Planning and Scheduling
%< 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 399-410
%8 2018-05-08
%D 2018
%R 10.1007/978-3-319-89743-1_35
%K Scheduling
%K Flow shop
%K Pachycondyla apicalis algorithm
%K Hybridization
%K Optimization
%K Metaheuristic
%Z Computer Science [cs]Conference papers
%X In the last years, many hybrid metaheuristics and heuristics combine one or more algorithmic ideas from different metaheuristics or even other techniques. This paper addresses the hybridization of a primitive ant colony algorithm inspired from the Pachycondyla apicalis behavior to search prey with the Genetic Algorithm to find near optimal solutions to solve the Flow Shop Scheduling Problem with makespan minimization. The developed algorithm is applied on different flow shop examples with diverse number of jobs. A sensitivity analysis was performed to define a good parameter choice for both the hybrid metaheuristic and the classical Genetic Algorithm. Computational results are given and show that the developed metaheuristic yields to a good quality solutions.
%G English
%Z TC 5
%2 https://inria.hal.science/hal-01913888/document
%2 https://inria.hal.science/hal-01913888/file/467079_1_En_35_Chapter.pdf
%L hal-01913888
%U https://inria.hal.science/hal-01913888
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-CIIA
%~ IFIP-AICT-522