中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2016, Vol. 35 ›› Issue (6): 171-176.DOI: 10.3969/j.issn.16740696.2016.06.35

• 其它 • 上一篇    

考虑碳交易的果蔬品供应链网络优化

严南南,朱丽珊   

  1. (上海海事大学 物流研究中心,上海 201306)
  • 收稿日期:2015-09-17 修回日期:2015-12-03 出版日期:2016-12-25 发布日期:2016-12-29
  • 作者简介:严南南(1968—),女,湖北鄂州人,副教授,博士,主要从事智能信息处理、物流系统优化方面的研究。Email:nnyan68@163.com。
  • 基金资助:
    上海市科委科技创新项目(12595810200)

Network Optimization of Fruit and Vegetable Supply Chain Considering Carbon Trading

YAN Nannan, ZHU Lishan   

  1. (Logistics Research Center, Shanghai Maritime University, Shanghai 201306, P. R. China)
  • Received:2015-09-17 Revised:2015-12-03 Online:2016-12-25 Published:2016-12-29
  • Contact: 朱丽珊(1992—),女,江西萍乡人,硕士,主要从事物流与供应链管理方面的研究。Email:2994945536@qq.com。

摘要: 基于供应链网络,分析了碳交易政策对果蔬品供应链总成本的影响,构建包括生产成本、运输成本、储存成本、腐败成本和碳交易成本在内的供应链成本函数。以最小化供应链成本和碳排放量为目标,建立多目标整数规划模型;针对总成本最低的均衡优化模型,采用粒子群算法进行求解,并对碳交易价格、车容量、单位耗油量等参数进行敏感性分析;算例验证了供应链网络模型和求解算法的可行性。实验结果显示:增加较少的成本能大幅度降低碳排放量,实现经济和环境的协调发展。

关键词: 管理工程, 碳交易, 节能减排, 果蔬品, 多目标规划, 粒子群算法

Abstract: Based on the supply chain network, the impact of carbon trading policy on the total cost of fruit and vegetable supply chain was researched, and a supply chain cost function was established, which included product cost, transport cost, storage cost, rot cost and carbon trading cost. In order to minimize the total cost and carbon emissions, a multiobjective integer programming model was established. For the balanced and optimized model with the lowest total cost, the particle swam optimization was used to solve, and the sensitivities of parameters such as carbon trading price, vehicle capacity and unit fuel consumption were analyzed. The case study proves the feasibility of the supply chain network model and the algorithm. The experiment results show that fewer increase of the cost can greatly reduce the carbon emissions to realize the harmonious development of economy and environment.

Key words: management engineering, carbon trading, energy saving and emission reduction, fruit and vegetable, multiobjective programming, particle swarm optimization

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