Work

Multi-objective Optimization of Low-carbon Cold Chain Logistics Routing Based on Improved Sparrow Search Algorithm

Year: 2024

Type: conference-paper

Abstract: To optimize the transportation efficiency of cold chain logistics and pursue the low-carbon goal of energy conservation and emission reduction, this paper delves into the multi-objective low-carbon cold chain vehicle routing problem. Compared with existing literature, this paper considers more environmentally friendly electric logistics vehicles and establishes an optimization model aimed at minimizing comprehensive costs and maximizing satisfaction. The comprehensive costs include vehicle fixed costs, transportation costs, charging costs, penalty costs, cargo damage costs, and carbon emissions. To accommodate the model's unique characteristics, a customized and enhanced Sparrow Search Algorithm has been devised to tackle the problem. Furthermore, the Genetic Algorithm has been employed to optimize the two objectives independently, thereby confirming the proficiency of both the model and the algorithm.

Source: International Conference on Big Data, Artificial Intelligence and Risk Management (ICBAR)

DOI: 10.1145/3718751.3718793

Authors: Can Cui, Bo Zhang, Ao Shen

Institution: Shenyang University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: bronze

OpenAlex ID: W4409868714

FWCI:

Cites: 7

Cited by:

Related to: 10