Research on Distribution Optimization of Emergency Perishable Materials Considering Periodic Changes in Freshness

Abstract

The distribution of emergency perishable materials is crucial for rescue operations in disaster-stricken areas. However, the freshness of these materials changes over time, affecting the quantity of materials that can be distributed to demand points at different stages. To address this issue, this paper proposes a novel approach. Firstly, a piecewise function is constructed to describe the impact of freshness on the quality and quantity of emergency perishable materials at different time stages. Secondly, the paper establishes a vehicle distribution optimization model with the goal of maximizing the sum of the freshness of all emergency perishable materials delivered to different disaster-affected locations, taking into account the different minimum freshness constraints for the same kind of materials in different locations. Thirdly, an approximate algorithm is designed to solve the model, with the time complexity and the upper and lower bounds of the approximate ratio analyzed. Finally, an example analysis is conducted to demonstrate the validity of the proposed model and algorithm.

Optimization of power material distribution route based on hybrid ant colony algorithm

“…Zhu et al [2] proposed a distribution model based on robust uncertainty by considering the deep robust uncertainty strategy problem for the emergency material distribution system under the information incompleteness environment. Zhang [3] established an optimization model for vehicle distribution of emergency perishable materials with the objective of maximizing the sum of freshness of all emergency perishable materials delivered to the demand nodes. Sheu [4] introduced a fuzzy clustering algorithm for coping with collaborative distribution of emergency logistics in times of emergency relief.…”