Affiliation:
1. School of Economics & Management, Beijing Information Science & Technology University, Beijing 100192, China
2. Beijing International Science and Technology Cooperation Base for Intelligent Decision and Big Data Application, Beijing 100192, China
Abstract
The low-carbon economy and sustainable development have become a widespread consensus. Chain supermarkets should pay attention to path optimization in the process of distribution to reduce carbon emissions. This study takes chain supermarkets as the research object, focusing on the optimization of the vehicle routing problem (VRP) in supermarket store distribution. Firstly, based on the concept of cost-effectiveness, we constructed a green and low-carbon distribution route optimization model with the lowest cost. With cost minimization as the objective function, the total distribution cost in the vehicle delivery process includes fixed cost, transportation cost, and carbon emission cost. The carbon emission cost is calculated using the carbon tax mechanism. Secondly, through integrating the Floyd algorithm, the nearest neighbor algorithm, and the insertion algorithm, a fusion heuristic algorithm was proposed for model solving, and an empirical study was conducted using the W chain supermarket in Wuhan as an example. The experimental results show that optimizing distribution routes considering carbon emission cost can effectively reduce carbon emissions. At the same time, it can also reduce the total costs of enterprises and society, thereby achieving greater social benefits at lower costs. The research results provide effective suggestions for chain supermarkets to control carbon emissions during the distribution process.
Funder
The Project of Cultivation for young top-motch Talents of Beijing Municipal Institutions
Beijing Key Lab of Big Data Decision Making for Green Development
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
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