Interactive fuzzy stochastic multi-level 0-1 programming using tabu search and probability maximization
Interactive fuzzy stochastic multi-level 0-1 programming using tabu search and probability maximization
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DOI：
10.1016/j.eswa.2013.10.027
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发表时间：
2014-05
期刊：
影响因子：
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通讯作者：
M. Sakawa;Takeshi Matsui
中科院分区：
文献类型：
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作者：
M. Sakawa;Takeshi Matsui
本文研究了目标函数和约束条件均为随机变系数的多层0-1规划问题的交互式模糊规划。根据概率最大化模型和机会约束的概念，将随机多层0-1规划问题转化为确定性问题。考虑到决策者判断的准确性，我们提出了交互式模糊规划。在所提出的交互式方法中，在确定各级决策者的模糊目标后，通过更新决策者的满意度，并考虑各层次之间的总体满意平衡，有效地得到满意的解决方案。为了有效地解决转换后的确定性问题，我们还引入了新的禁忌搜索一般0-1规划问题。一个三层0-1规划问题的数值例子来说明所提出的方法。
In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.