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基于遗传算法的生鲜冷链物流配送路径优化。

The Optimization of Distribution Path of Fresh Cold Chain Logistics Based on Genetic Algorithm.

机构信息

Shijiazhuang Posts and Telecommunications Technical College, Shijiazhuang, Hebei 050021, China.

出版信息

Comput Intell Neurosci. 2022 Aug 1;2022:4667010. doi: 10.1155/2022/4667010. eCollection 2022.

DOI:10.1155/2022/4667010
PMID:35958774
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9359830/
Abstract

The products of the enterprise are the logistics objects of the enterprise. Therefore, the company's products are the primary factor affecting logistics costs. The products of different enterprises may be different in terms of the type, nature, volume, quality, and physical and chemical properties of the products, which will have different impacts on the cost of logistics activities such as warehousing, transportation, and material handling of enterprises. More and more enterprises have taken the cost of logistics distribution as one of the important indicators affecting the development of enterprises; especially, cold chain logistics has been rapidly developed and valued in recent years, because the requirements of such products for delivery time, distribution efficiency, and distribution environment are very strict, whether the goods can be distributed in a standard and reasonable environment and whether the delivery vehicle can deliver the goods within the time specified by the customer have greatly affected the safety of frozen and refrigerated food. Therefore, this paper reduces the cost of the distributor through the optimization of the distribution path of cold chain logistics and makes the goods distributed can be delivered to the customer faster and more reasonably by establishing an integrated optimization platform, which is of great significance for how to reduce the cost of enterprises. Therefore, this paper starts from the function with the lowest distribution cost as the goal, comprehensively considers the specific characteristics of cold chain logistics, given the relevant constraints, uses the improved genetic algorithm to iterate on the given scheme, sends the improved new scheme to the simulation software for simulation operation, then sends the results obtained by the operation to the genetic algorithm for the next iteration, and repeats it in turn until the prespecified conditions can be terminated. Therefore, this paper summarizes some problems and development status in cold chain logistics and distribution routes by consulting relevant literature, optimizes the scheme by using VRP model combined with constraints, establishes a distribution system model, and finally verifies and analyzes to obtain a more reasonable and satisfactory solution. The innovation of this paper is that the research on the VRP problem is optimized through an improved genetic algorithm, certain improvements have been made in the coding method and the operation of selection, crossover, variation, etc., and the improved genetic algorithm can greatly reduce the number of program iterations. Then, we use the integrated optimization platform to import the solution into FlexSim for simulation, each simulation of the new solution will be transmitted to MATLAB through the Excel table for the next optimization iteration, and we repeat the above steps until the preset conditions are met after the termination. This would lead to a more realistic and satisfactory solution.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/8f555458d2e6/CIN2022-4667010.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/7f45f135e372/CIN2022-4667010.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/3ea3c05ad3c6/CIN2022-4667010.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/0745c45de699/CIN2022-4667010.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/024e2d191e75/CIN2022-4667010.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/8f555458d2e6/CIN2022-4667010.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/7f45f135e372/CIN2022-4667010.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/3ea3c05ad3c6/CIN2022-4667010.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/0745c45de699/CIN2022-4667010.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/024e2d191e75/CIN2022-4667010.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1a6f/9359830/8f555458d2e6/CIN2022-4667010.005.jpg
摘要

企业的产品是企业物流的对象。因此,公司的产品是影响企业仓储、运输和物料搬运等物流活动成本的主要因素。不同企业的产品在产品类型、性质、体积、质量、理化性质等方面可能存在差异,这将对企业的物流成本产生不同的影响。越来越多的企业将物流配送成本作为影响企业发展的重要指标之一;特别是近年来,冷链物流发展迅速并受到重视,因为此类产品对交货时间、配送效率和配送环境的要求非常严格,货物能否在标准合理的环境中配送,以及运输车辆能否在客户规定的时间内将货物送达,都极大地影响了冷冻冷藏食品的安全性。因此,本文通过优化冷链物流配送路径来降低分销商的成本,并通过建立集成优化平台,使货物能够更快、更合理地配送给客户,这对如何降低企业成本具有重要意义。因此,本文从以最低配送成本为功能目标出发,综合考虑冷链物流的具体特点,在满足相关约束条件的情况下,采用改进的遗传算法对给定方案进行迭代,将改进后的新方案发送到仿真软件进行仿真运算,然后将运算结果发送给遗传算法进行下一次迭代,依次重复,直到满足预设条件为止。因此,本文通过查阅相关文献,总结了冷链物流及配送路线中的一些问题和发展现状,通过 VRP 模型与约束相结合的方法对方案进行优化,建立了配送系统模型,最后进行验证和分析,得出了更合理、更满意的解决方案。本文的创新之处在于,通过改进的遗传算法对 VRP 问题进行优化,在编码方法和选择、交叉、变异等操作方面进行了一定的改进,大大减少了程序迭代次数。然后,我们使用集成优化平台将解决方案导入 FlexSim 进行仿真,每次对新解决方案的仿真都会通过 Excel 表格传输到 MATLAB 进行下一次优化迭代,直到满足预设条件后再终止。这样可以得到更真实、更满意的解决方案。

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e-Graphene: A Computational Platform for the Prediction of Graphene-Based Drug Delivery System by Quantum Genetic Algorithm and Cascade Protocol.电子石墨烯:一种通过量子遗传算法和级联协议预测基于石墨烯的药物递送系统的计算平台。
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