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首页> 外文期刊>Procedia Computer Science >Multiobjective Two-level Simple Recourse Programming Problems with Discrete-type LR Fuzzy Random Variables
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Multiobjective Two-level Simple Recourse Programming Problems with Discrete-type LR Fuzzy Random Variables

机译：不同型LR模糊随机变量的多目标两级简单追索程序编程问题

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In this paper, we focus on multiobjective two-level simple recourse programming problems with discrete-type LR fuzzy random variables, in which each of the decision makers called the leader and the follower optimizes his/her multiple objective functions independently, shortages and excesses arising from the violation of the constraints with discrete-type LR fuzzy random variables are penalized, and the sum of the objective function and the expectation of the amount of the penalties is minimized. To deal with such problems, we introduce a new solution concept called an estimated Pareto Stackelberg solution for the leader. To obtain a candidate of a satisfactory solution for the leader from among an estimated Pareto Stackelberg solution set, using the Kuhn-Tucker approach and the transformation technique for complementarity conditions, an original problem is transformed into a mixed integer programming problem. Then, we propose an interactive algorithm to obtain a satisfactory solution of the leader from among an estimated Pareto Stackelberg solution set. A numerical example illustrates the proposed algorithm for a multiobjective two-level fuzzy random simple recourse programming problem under the hypothetical leader.
机译：在本文中，我们专注于多目标二级简单追索程序编程问题，其中包括离散类型的LR模糊随机变量，其中每个决策者称为领导者和追随者独立优化他/她的多目标功能，产生的短缺和过度从违反离散型LR模糊随机变量的违法行为受到处罚的惩罚，目标职能和罚款金额的总和最小化。要处理此类问题，我们介绍了一个名为估计帕累托Stackelberg解决方案的新解决方案概念。为了从估计的帕累托Stackelberg解决方案集中获得令人满意的解决方案的候选解决方案，使用Kuhn-Tucker方法和用于互补条件的转换技术，将原始问题转换为混合整数编程问题。然后，我们提出了一种交互式算法，以从估计的帕累托Stackelberg解决方案集中获得领导者的令人满意的解决方案。数字示例说明了假设领导者下的多目标二级模糊随机简单追索程序编程问题的所提出的算法。

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