不确定条件下环境友好型资源分配二层规划模型
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  • 英文篇名:Environmental Friendly Bi-level Resource Allocation Programming under Uncertain Condition
  • 作者:周晓阳 ; 涂燕 ; 韩菁
  • 英文作者:ZHOU Xiao-yang;TU Yan;HAN Jing;School of Economics and Management,Xidian University;School of Management,Wuhan University of Technology;International Business School,Shaanxi Normal University;
  • 关键词:资源分配 ; 不确定条件 ; 环境友好 ; 二层规划
  • 英文关键词:resource allocation;;uncertain condition;;environmental friendly;;bi-level programming
  • 中文刊名:YCGL
  • 英文刊名:Operations Research and Management Science
  • 机构:西安电子科技大学经济与管理学院;武汉理工大学管理学院;陕西师范大学国际商学院;
  • 出版日期:2018-05-25
  • 出版单位:运筹与管理
  • 年:2018
  • 期:v.27;No.146
  • 基金:国家自然科学基金资助项目(71401093,71403158)
  • 语种:中文;
  • 页:YCGL201805004
  • 页数:7
  • CN:05
  • ISSN:34-1133/G3
  • 分类号:19-25
摘要
本文讨论了不确定条件下环境友好型的资源分配问题:其中总公司作为上层领导者在各下属工厂间合理分配资源,以期获得最大收益的同时降低对环境的污染程度;而作为下层从属者的各工厂决定各自产量以期获得最大利润。该问题中的产品价格、生产成本、资源成本等被考虑为随机变量,环境污染指数被考虑为模糊变量,因而本文构造了不确定条件下的机会约束二层资源分配模型。运用等价定理对模型进行转换,并采用交互式满意度法将二层模型转化为单层模型以便求解。最后通过数值算例证实了模型和算法的可行性与有效性。此外,由于模型含有影响模型解的参数,故基于满意度和置信水平分别进行了灵敏度分析,进一步验证了所提出模型的科学性。
        In this paper,we discuss the environmental friendly resource allocation problem under the uncertain condition,where the leader is the head office,who allocates the resource properly to maximize the profit and minimize the pollution; the follower is the processing plants,who decide the production amount of every products to get their best profit. In this problem,we suggest that the products' price,the capacity and the cost obey random distribution,and the environment pollution factors are fuzzy variables. Based on the above statement,an uncertain chance constrained bi-level resource allocation model is constructed. In order to make the model solvable,we then convert the uncertain model into the equivalent model,and adopt the interactive satisfied method to transform the bi-level model into a kind of single level model. At last,we use a numerical example to test and verify the feasibility and efficiency of the model and the solution method. Besides,there are confidence levels and satisfied degrees in the models which may affect the result to some extent,hence we also proceed the sensitivity analysis to show the relationship between the result and the confidence levels and satisfied degrees,respectively.
引文
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