%0 Journal Article
%T Permutation flow shop scheduling problem under non-renewable resources constraints
%+ Manufacturing engineering laboratory of Tlemcen (MELT)
%+ Laboratoire d'Optimisation des SystÃ¨mes Industriels (LOSI)
%A Laribi, Imane
%A Yalaoui, Farouk
%A Sari, Zaki
%< avec comitÃ© de lecture
%@ 2040-3607
%J International Journal of Mathematical Modelling and Numerical Optimisation
%I Inderscience
%V 9
%N 3
%P 254
%8 2019
%D 2019
%R 10.1504/IJMMNO.2019.100494
%K scheduling
%K non-renewable resources
%K optimisation
%K mathematical programming
%K genetic algorithm
%K local search
%K permutation flow shop
%Z Computer Science [cs]/Operations Research [cs.RO]
%Z Computer Science [cs]/Data Structures and Algorithms [cs.DS]
%Z Mathematics [math]/Optimization and Control [math.OC]Journal articles
%X The majority of flow shop scheduling problems considers machines as the only resource. However, in most real-life manufacturing environments, jobs for their processing on machines may require additional non-renewable resources. Considering such resources, the scheduling problem is more realistic and much harder to solve. In this paper, we investigate the permutation flow shop scheduling problem subject to non-renewable resources constraints. The objective is to find a schedule that minimises the maximum completion time. An integer linear programming model is developed. Because of the computation time constraint, we propose an approximate resolution method based on genetic algorithm. To obtain better and more robust solutions, the Taguchi method is performed for tuning the parameters and operators of the algorithm. Furthermore, a local search is proposed to enhance the searching ability. Finally, computational experiments are conducted to evaluate the performance of both mathematical model and algorithm on different configurations of non-renewable resources availability.
%G English
%L hal-02502522
%U https://utt.hal.science/hal-02502522
%~ CNRS
%~ UNIV-TROYES
%~ INSMI
%~ TDS-MACS
%~ UTT
%~ LOSI