辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2011, Vol. 31 ›› Issue (2): 90-94.DOI: 10.3696/j.issn.1672-6952.2011.02.023

• 其他学科 • 上一篇    

一种使用遗传算法进行物流配送成本优化方法

毕浅雨,李艳杰* ,李 飒   

  1. 辽宁石油化工大学经济管理学院,辽宁抚顺113001
  • 收稿日期:2011-03-07 出版日期:2011-06-25 发布日期:2017-07-05
  • 作者简介:毕浅雨(1983—),男,山东淄博市,在读硕士。

A Kind of Method for Logistics Distribution Cost Optimization Based on Genetic Algorithm

BI Qian-yu， LI Yan-jie*， LI Sa   

  1. School of Economics and Management, Liaoning Shihua University, Fushun Liaoning 113001, P.R.China
  • Received:2011-03-07 Published:2011-06-25 Online:2017-07-05

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摘要： 在物流配送业务中,配送成本的优化是降低企业成本、提高经济效益的关键。根据物流配送业务的
特点,建立了成本优化模型。该模型将同一客户需求的货物分成急需货物和普通货物,在有时间要求和运力有限的
情况下,这种货物分类处理的方式为降低配送成本提供了新思路。在此基础上,构建了成本优化遗传算法,给出了
算法实现的具体方法、步骤。实例计算结果表明,该方法能快速、高效地收敛于一个优异的解,在物流配送成本优化
中能获得较好的优化结果。

关键词: 物流配送 ,  , 遗传算法 ,  , 成本优化

Abstract:  

In the business of logistics distribution, the key is cost optimization which could reduce cost and increase economic returns. According to the character of logistics distribution, the model of cost optimization was set up .The model separated the cargo for one customer into common cargo and urgent cargo , which offered a new idea to reduce distribution cost under the conditions of crash time and the transportation capacity limited. On the basis of this model, the cost optimization genetic algorithm was created and is a specific method and process to apply the algorithm . Actual example shows that the method can get convergence to an outstanding solution fast and efficiently.Therefore this method can get better optimization result during cost optimization of logistics distribution.

Key words: Logistics distribution  ,  ,  Genetic algorithm  ,  , Cost optimization

引用本文

毕浅雨,李艳杰,李 飒. 一种使用遗传算法进行物流配送成本优化方法[J]. 辽宁石油化工大学学报, 2011, 31(2): 90-94.

BI Qian-yu，LI Yan-jie，LI Sa. A Kind of Method for Logistics Distribution Cost Optimization Based on Genetic Algorithm[J]. Journal of Liaoning Petrochemical University, 2011, 31(2): 90-94.

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链接本文: http://journal.lnpu.edu.cn/CN/10.3696/j.issn.1672-6952.2011.02.023

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