HIERARCHICAL MULTIOBJECTIVE STOCHASTIC L INEAR PROGRAMMING PROBLEMS BASED ON THE FUZZY DECISION
HIERARCHICAL MULTIOBJECTIVE STOCHASTIC L INEAR PROGRAMMING PROBLEMS BASED ON THE FUZZY DECISION
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基于模糊决策的层次多目标随机线性规划问题
DOI：
10.1142/9789814390019_0001
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Kota Matsui
中科院分区：
文献类型：
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作者：
H. Yano;Kota Matsui
在本文中，我们重点研究分层多目标随机线性规划问题（HMOSLP），其中分层组织中的多个决策者拥有自己的多个目标线性函数以及共同的线性约束。为了处理 HMOSLP，应用了概率最大化模型。通过考虑概率最大化模型中允许目标水平与相应概率函数值之间的冲突，假设每个决策者指定的不是他/她自己的允许目标水平，而是他/她自己的允许目标水平和相应概率函数的隶属函数。导出隶属函数后，通过模糊决策提出获得满意解的交互算法，通过决策权体现层次决策结构，在允许的目标水平和相应的概率函数之间达到适当的平衡。通过说明性数值示例来演示交互过程。
In this paper, we focus on hierarchical multiobjective stochastic linear programming problems (HMOSLP) where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. In order to deal with HMOSLP, a probability maximization model is applied. By considering the conflict between permissible objective levels and the values of the corresponding probability function in a probability maximization model, it is assumed that each of the decision maker specifies not his/her own permissible objective levels but the membership functions of both his/her own permissible objective levels and the corresponding probability functions. After eliciting membership functions, the interactive algorithm to obtain a satisfactory solution is proposed through the fuzzy decision, in which the hierarchical decision structure is reflected through the decision power and the proper balance between permissible objective levels and the corresponding probability function is attained. Interactive processes are demonstrated by means of an illustrative numerical example.