Work

Optimization of Fresh Food Logistics Routes for Heterogeneous Fleets in Segmented Transshipment Mode

Year: 2024

Type: article

Abstract: To address the challenges of environmental impact and distribution efficiency in fresh food logistics, a segmented transshipment model involving the coordinated operation of gasoline and electric vehicles is proposed. The model minimizes total distribution costs by considering transportation, refrigeration, product damage, carbon emissions, and penalties for time window violations. The k-means++ clustering algorithm is used to determine transshipment points, while an improved adaptive multi-objective ant colony optimization algorithm (IAMACO) is employed to optimize the delivery routes for the heterogeneous fleet. The case study results show that compared to the traditional model, the segmented transshipment mode reduces the total distribution costs, carbon emissions, and time window penalty costs by 22.13%, 28.32%, and 41.08%, respectively, providing a viable solution for fresh food logistics companies to achieve sustainable and efficient growth.

Source: Mathematics

DOI: 10.3390/math12233831

Authors: Haoqing Sun, Manhui He, Yanbing Gai, Jinghao Cao

Institutions: Liaoning Technical University, Bohai Shipbuilding Vocational College, Nanjing University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: gold

Estimated APC paid: $2,955