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A Fuzzy Programming Method for Solving Multiobjective Chance Constrained Programming Problems Involving Log-Normally Distributed Fuzzy Random Variables

机译:一种求解多目标机会的模糊编程方法,限制了涉及日志正常分布的模糊随机变量的编程问题

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In this paper a fuzzy programming technique is presented to solve multiobjective chance constrained programming problem having the right sided parameters associated with system constrains follow log-normal distribution. In model formulation process the imprecise probabilistic problem is converted into an equivalent fuzzy programming model by applying chance constrained programming methodology. Then by considering fuzzy nature of parameters involved with the system constraints, the problem is decomposed on the basis of tolerance values of the parameters. The individual optimal value of each objective is found to construct the membership goals of the objectives. A priority based fuzzy goal programming approach is used for achievement of the highest membership degree to the extent possible under different priority structures to achieve the ideal point dependent solution in the decision making context. To expound the potentiality of the proposed approach, an illustrative example is solved and the solution is compared with other existing technique.
机译:在本文中,提出了一种模糊编程技术来解决具有与系统相关联的右侧参数的多目标机会约束编程问题,遵循日志正态分布。在模型制构过程中,通过施加约束编程方法,通过应用机会转换为等效模糊编程模型的不精确概率问题。然后,通过考虑与系统约束所涉及的参数的模糊性质,问题基于参数的公差值分解。发现每个目的的个人最佳价值构建目标的成员国。基于优先级的模糊目标编程方法用于在不同优先级结构下实现最高的成员程度,以实现决策背景下的理想点依赖性解决方案。为了阐述所提出的方法的潜力,解决了说明性示例,并将解决方案与其他现有技术进行了比较。

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