基于改进蚁群算法的低碳冷链配送路径优化
Optimization on Cold Chain Distribution Routes Considering Carbon Emissions Based on Improved Ant Colony Algorithm
鲍惠芳 1方杰 1张进思 1王传胜1
作者信息
- 1. 皖西学院 电气与光电工程学院,安徽 六安 237012
- 折叠
摘要
针对目前冷链配送路径优化中存在的综合配送成本考虑不全面的问题,根据生鲜配送特点,综合考虑基本运输成本、碳排放、制冷、货损以及时间窗约束,建立以综合配送成本最小化为目标的路径优化模型.提出改进蚁群算法对该优化模型进行求解,在初始阶段使用遗传算法生成初期信息素分布,而后使用蚁群算法进行后续寻优搜索,再引入模拟退火算法的Metropolis准则筛选优质解.通过仿真实验验证了优化模型和改进算法的有效性,对低碳可持续发展理念下生鲜品冷链配送路径优化问题研究具有一定意义,助力冷链运输行业向低碳经济转型.
Abstract
As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization,this paper builds a path optimization model to minimize the comprehensive distribution cost.The model combines with the characteristics of fresh distribution,and comprehensively considers the transportation cost,carbon emission,refrigeration,cargo damage and time window constraints during cold chain transportation.Then,an improved ant colony algorithm is designed to solve this model.At the initial stage,the genetic algorithm is adopted to generate the initial pheromone,and then the ant colony algorithm is applied to conduct the subsequent optimization search.The Metropolis criterion of the simulated annealing algorithm is introduced to screen the high-quality solution.Finally,the effectiveness of the proposed optimization model and improved algorithm is verified by several experiments.The proposed model and improved algorithm have a certain significance for the research on the optimization of the cold chain distribution route of fresh food under the concept of low-carbon sustainable development.They helps the cold chain transportation industry to transition to low-carbon economy.
关键词
冷链配送/优化模型/改进蚁群算法/低碳Key words
cold chain distribution/optimization model/improved ant colony algorithm/low-carbon引用本文复制引用
基金项目
安徽省教育厅重点项目(2022AH051675)
皖西学院自然重点项目(WXZR202015)
皖西学院青年项目(WXZR202120)
出版年
2024
NETL
NSTL
维普
万方数据