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Optimization of logistics systems using metaheuristic based hybridization techniques

Abstract : In the postwar years, the development of operational research provided companies tools to deal with their logistic problems in a quantitative way. For a long time, these problems were split into unrelated sub-problems, each sub-problem being often separately tackled. This is mainly due to the fact that considered sub-problems, such as localization problem, planning problem, scheduling problem or transportation problem are generally NP-hard problems and their computational complexity is still a significant issue for many researchers. Nevertheless, in an increasingly competitive industrial environment, companies continue to have a strong demand for decision aid tools able to get a global view of their organization. The aim of this chapter is to present the challenges of such a vision, to understand the consequences in terms of logistics system modeling and to state on new optimization techniques. This chapter is organized as follows. The first part describes logistics systems in general and supply chain in particular. In this part, concepts of horizontal and vertical synchronization to allow a comprehensive vision of supply chain is developed. We also show that metaheuristic based hybridization techniques are especially suitable to logistics system characteristics. The second part is devoted to hybridiza-tion techniques: metaheuristic / optimization method and metaheuristic / evaluation model. In the last part, we present some issues about synchronization as well as hybridization methods proposed in the literature.
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Contributor : Nathalie Grangeon Connect in order to contact the contributor
Submitted on : Wednesday, March 10, 2021 - 2:58:36 PM
Last modification on : Thursday, June 17, 2021 - 1:50:23 PM
Long-term archiving on: : Friday, June 11, 2021 - 6:01:10 PM



  • HAL Id : hal-02023692, version 1



Laurent Deroussi, Nathalie Grangeon, Sylvie Norre. Optimization of logistics systems using metaheuristic based hybridization techniques. Metaheuristics, 2016. ⟨hal-02023692⟩



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