Work

Optimization of low-carbon fresh food cold chain logistics distribution path considering dynamic demand with multiple vehicle types

Year: 2025

Type: conference-paper

Abstract: To address high distribution costs and low vehicle utilisation from irrational dynamic demand processing in multi-model cold chain distribution, a dynamic update route strategy is proposed. This study constructs a two-stage multi-model vehicle route optimisation model for periodic dynamic order processing, using an improved genetic algorithm for solution. The goal is to minimise costs, ensure quick customer response, and achieve energy savings and emission reduction. An enhanced genetic algorithm determines the initial distribution scheme in the static phase, while a two-phase key time points strategy updates routes dynamically. Compared to direct additional vehicle distribution, the model reduces overall costs by 25.34%, optimises carbon emission costs by 35.24%, and reduces the number of vehicles by 33.33%, effectively lowering total distribution costs and improving efficiency.

Source: International Conference on Computer Information and Big Data Applications (CIBDA)

DOI: 10.1145/3746709.3746822

Authors: Zejuan Huang, Ling Zhang, Xiaochuan Shen

Institutions: Wuhan University of Science and Technology, Wuhan Donghu University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Climate action, Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W4413845198

FWCI:

Cites: 4

Cited by:

Related to: 10