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Technical Note: A goal programming approach for fuzzy multiobjective fractional programming problems

机译:技术说明:一种用于模糊多目标分数规划问题的目标规划方法

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摘要

Fuzzy multiple objective fractional programming (FMOFP) is an important technique for solving many real-world problems involving the nature of vagueness, imprecision and/or random. Following the idea of binary behaviour of fuzzy programming (Chang 2007), there may exist a situation where a decision-maker would like to make a decision on FMOFP involving the achievement of fuzzy goals, in which some of them may meet the behaviour of fuzzy programming (i.e. level achieved) or the behaviour of binary programming (i.e. completely not achieved). This is turned into a fuzzy multiple objective mixed binary fractional programming (FMOMBFP) problem. However, to the best of our knowledge, this problem is not well formulated by mathematical programming. Therefore, this article proposes a linearisation strategy to formulate the FMOMBFP problem in which extra binary variable is not required. In addition, achieving the highest membership value of each fuzzy goal defined for the fractional objective function, the proposed method can alleviate the computational difficulties when solving the FMOMBFP problem. To demonstrate the usefulness of the proposed method, a real-world case is also included.
机译:模糊多目标分数规划(FMOFP)是解决许多实际问题的重要技术,这些问题涉及模糊性,不精确性和/或随机性。遵循模糊规划的二进制行为的思想(Chang 2007),决策者可能希望就涉及模糊目标实现的FMOFP做出决策,其中有些可能满足模糊行为。编程(即达到级别)或二进制编程的行为(即完全没有达到)。这变成了模糊多目标混合二进制分数规划(FMOMBFP)问题。但是,据我们所知,这个问题不能通过数学编程很好地解决。因此,本文提出了一种线性化策略来公式化FMOMBFP问题,其中不需要额外的二进制变量。另外,为实现分数目标函数定义的每个模糊目标的最高隶属度值,该方法可以缓解解决FMOMBFP问题时的计算困难。为了证明所提出方法的有效性,还包括一个实际案例。

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