4.7 Article

A time-expanded network reduction matheuristic for the logistics service network design problem

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2020.102203

关键词

Logistics; Service network design; Dynamic discretization discovery; Integer programming; Heuristics

资金

  1. French National Research Agency through the Pi-Comodalite project [ANR-15-CE22-0012]
  2. Agence Nationale de la Recherche (ANR) [ANR-15-CE22-0012] Funding Source: Agence Nationale de la Recherche (ANR)

向作者/读者索取更多资源

This study investigates the operations of a 3PL service provider in the supply chain management of a French restaurant chain, using a new network reduction heuristic algorithm to solve the Logistics Service Network Design Problem. Experimental results demonstrate the efficiency of the proposed approach and its alignment with practical operational needs, while also uncovering the impact of distribution strategies on transportation planning and logistics costs.
Planning cost-effective logistics operations involve the integration of multiple decision-making levels. In the domain of supply chain management, the last decades have seen the emergence of 3PL service providers that specialize in integrating warehousing and transportation services. In this paper, we study the operations performed by a 3PL service provider in the supply chain management of a French restaurant chain. The transportation planning process is assisted by solving the Logistics Service Network Design Problem (LSNDP). As realistic instances are too large for on-the-shelf optimization solvers to solve in acceptable run-times, we develop a network reduction heuristic inspired by the recent Dynamic Discretization Discovery algorithm. Through an extensive series of experiments carried out on instances based on the operations of an industrial partner, we demonstrate the efficiency of the proposed approach. We also investigate the impact of the distribution strategy used in practice to determine the transportation plan and how this distribution strategy can be modified to reduce the overall logistics costs.

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