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Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems

机译:交互式TOPSIS算法,用于解决多级非线性多目标决策问题

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This paper extended the concept of the technique for order preference by similarity to ideal solution (TOPSIS) to develop a methodology for solving multi-level non-linear multi-objective decision-making (MLN-MODM) problems of maximization-type. Also, two new interactive algorithms are presented for the proposed TOPSIS approach for solving these types of mathematical programming problems. The first proposed interactive TOPSIS algorithm includes the membership functions of the decision variables for each level except the lower level of the multi-level problem. These satisfactory decisions are evaluated separately by solving the corresponding single-level MODM problems. The second proposed interactive TOPSIS algorithm lexicographically solves the MODM problems of the MLN-MOLP problem by taking into consideration the decisions of the MODM problems for the upper levels. To demonstrate the proposed algorithms, a numerical example is solved and compared the solutions of proposed algorithms with the solution of the interactive algorithm of Osman et al. (2003) [4]. Also, an example of an application is presented to clarify the applicability of the proposed TOPSIS algorithms in solving real world multi-level multi-objective decision-making problems.
机译:本文通过类似于理想解决方案(TOPSIS)的方法扩展了顺序偏好技术的概念,以开发一种用于解决最大化类型的多层非线性多目标决策(MLN-MODM)问题的方法。此外,针对拟议的TOPSIS方法,提出了两种新的交互式算法,用于解决这些类型的数学编程问题。首先提出的交互式TOPSIS算法包括除多级问题的较低级别之外的每个级别的决策变量的隶属函数。通过解决相应的单级MODM问题,可以分别评估这些令人满意的决策。第二种提出的交互式TOPSIS算法从字典上解决了MLN-MOLP问题的MODM问题,它考虑了上层MODM问题的决策。为了说明所提出的算法,解决了一个数值示例,并将所提出的算法的解决方案与Osman等人的交互式算法的解决方案进行了比较。 (2003)[4]。此外,给出了一个应用示例,以阐明所提出的TOPSIS算法在解决现实世界中多级多目标决策问题中的适用性。

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