Optimizing Fresh Agricultural Product Distribution Paths Under Demand Uncertainty

Chu, Jie ORCID: 0000-0001-7857-4176, Tan, Shiyan, Lin, Junyi, Chan, Jimmy Hing Tai, Lee, Louisa Yee Sum and Zheng, Leven J (2023) Optimizing Fresh Agricultural Product Distribution Paths Under Demand Uncertainty. Journal of Global Information Management, 31 (1). pp. 1-22.

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Abstract

<p>Consumers' demand for fresh agricultural products (FAPs) and their quality requirements are increasing in the current agricultural-product consumption market. FAPs' unique perishability and short shelf-life features mean a high level of delivery efficiency is required to ensure their freshness and quality. However, consumers' demand for FAPs is contingent and geographically dispersed. Therefore, the conflicting relationship between the costs associated with the logistics distribution and the level of delivery quality is important to consider. In this paper, the authors consider a fresh agricultural-product distribution path planning problem with time windows (FAPDPPPTW). To address the FAPDPPPTW under demand uncertainty, a mixed-integer linear programming model based on robust optimization is proposed. Moreover, a particle swarm optimization algorithm combined with a variable neighborhood search is designed to solve the proposed mathematical model. The numerical experiment results show the robustness and fast convergence of the algorithm.</p>

Item Type:	Article
Uncontrolled Keywords:	2 Zero Hunger
Divisions:	Faculty of Humanities and Social Sciences > School of Management
Depositing User:	Symplectic Admin
Date Deposited:	27 Oct 2023 07:37
Last Modified:	17 Mar 2024 18:03
DOI:	10.4018/jgim.326557
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3176479