Integrated Districting, Fleet Composition, and Inventory Planning for a Multi-Retailer Distribution System
Abstract
We study an integrated districting, fleet composition, and inventory planning problem for a multi-retailer distribution system. In particular, we analyze the districting decisions for a set of retailers such that the retailers within the same district share truck capacity for their shipment requirements. The number of trucks of each type dedicated to a retailer district and retailer inventory planning decisions are jointly determined in a district formation problem. We provide a mixed-integer-nonlinear programming formulation for this problem and develop a column generation based heuristic approach for its set partitioning formulation. To do so, we first characterize important properties of the optimal fleet composition and inventory planning decisions for a given retailer district. Then, we utilize these properties within a branch-and-price method to solve the integrated districting, fleet composition, and inventory planning problem. A set of numerical studies demonstrates the efficiency of the solution methods discussed for the investigated subproblems. An additional set of numerical studies compares the branch-and-price method to a commercial solver and an evolutionary heuristic method. Further numerical studies illustrate the economic as well as environmental benefits of the integrated modeling approach for various settings.
Recommended Citation
D. Konur and J. Geunes, "Integrated Districting, Fleet Composition, and Inventory Planning for a Multi-Retailer Distribution System," Annals of Operations Research, vol. 273, no. 1-2, pp. 527 - 559, Springer Verlag, Feb 2019.
The definitive version is available at https://doi.org/10.1007/s10479-016-2338-6
Department(s)
Engineering Management and Systems Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Distribution; Districting; Fleet composition; Inventory management
International Standard Serial Number (ISSN)
0254-5330; 1572-9338
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Springer Verlag, All rights reserved.
Publication Date
01 Feb 2019