2024

Chapitre de livre

In: Alharbi, I., Ben Ncir, CE., Alyoubi, B., Ben-Romdhane, H. (eds) Advances in Computational Logistics and Supply Chain Analytics. Unsupervised and Semi-Supervised Learning. Springer, Cham,129--147..

Bi-level optimization problems (BLOPs) is a class of challenging problems with two levels of optimization tasks. The particular structure of the bi-level optimization model facilitates the formulation of several practical situations that involve hierarchical decision-making process where lower-level decisions depend on upper-level actions. In this context, a hierarchical production–distribution (PD) planning problem in supply management is addressed. These two entities (production and distribution) are naturally related; however, in most practical situations, each decision entity concentrates on optimizing its process one at a time, independently on other related decisions. In this chapter, we considered a new formulation of the PD system using the bi-level framework under the constraints of shared depots resources in the distribution phase. To this end, a mixed integer bi-level formulation is proposed to model the problem, and a cooperative decomposition-based algorithm is developed to solve the bi-level model. Statistical experimental results show that our proposed algorithm gives competitive and better results with respect to the competitor algorithm. Indeed, allowing flexible choice of the stop depot reveals the outperformance of our proposal in reducing total traveling cost of generated solution compared to the baseline problem.

@incollection{chaabani2023solving,
  title={Solving hierarchical production--distribution problem based on MDVRP under flexibility depot resources in supply chain management},
  author={Chaabani, Abir and Ben Said, Lamjed},
  booktitle={Advances in Computational Logistics and Supply Chain Analytics},
  pages={129--147},
  year={2023},
  publisher={Springer}
}