摘要
针对TOPSIS法可能存在多个备选方案的接近度相同而无法进行全排序的问题。首先,考虑到等效方案在正、负理想解距离上的差异,本文将其细分为强等效方案(不同方案到理想解距离相等)与弱等效方案(不同方案到理想解距离的比值相等但距离不等)。其次,以二维目标为坐标系描述TOPSIS系统,发现TOPSIS评价系统中有:(1)所有方案均位于某一特定区域;(2)强等效方案为同一点,而弱等效方案则位于特定直线上等特性。进而,依据二维目标空间下等效方案与正、负理想解的相对位置关系,针对存在弱等效方案的TOPSIS评价系统,提出一种在依据接近度对备选方案进行分组与组间排序基础上,重新定义排序指数对组内等效方案实施排序。从而设计出一种组间排序基础上的组内排序与组间排序相结合的改进TOPSIS排序法。该方法既不改变方案的原有TOPSIS排序,又可实现弱等效方案的全排序。最后通过数值分析验证所提出方法的合理性和有效性。
In decision-making processes,the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)is a widely recognized multi-criteria decision analysis(MCDA)method.However,a significant challenge arises when multiple alternatives have identical ranking indices,particularly when these alternatives are located on the same multi-dimensional sphere.This leads to ambiguities in the ranking process,obscuring decision-making and reducing the clarity and utility of the TOPSIS method.Given the increasing complexity of decision-making environments in both theoretical and practical scenarios,there is a pressing need to refine the TOPSIS method to address this limitation.This paper aims to enhance the TOPSIS methodology by introducing a modified approach that effectively differentiates between strongly and weakly equivalent alternatives,thereby providing a more robust and clear ranking system.The proposed modification to the TOPSIS method involves several key steps to address the issue of equivalent alternatives.Firstly,this paper categorizes equivalent alternatives into strongly equivalent alternatives and weakly equivalent alternatives.Strongly equivalent alternatives are those where different alternatives have equal distances to the ideal solution,while weakly equivalent alternatives are those where the ratios of distances to the ideal solution are equal but the distances themselves are different.Using a two-dimensional target coordinate system to describe the TOPSIS system,the following characteristics are identified:(1)All alternatives are located in a specific region.(2)Strongly equivalent alternatives are at the same point,while weakly equivalent alternatives lie on a specific line.Based on the relative positions of equivalent alternatives and the positive and negative ideal solutions in the two-dimensional target space,a modified TOPSIS ranking method is proposed for evaluation systems with weakly equivalent alternatives.This method involves grouping and intergroup ranking of alternatives,and then redefining the ranking index to sort the equivalent alternatives within each group.The integration of intragroup and intergroup ranking forms a ranking sequence that achieves full ranking of systems with weakly equivalent alternatives,consistent with the classic TOPSIS method.The improved TOPSIS method retains the original ranking characteristics while enabling full ranking of weakly equivalent alternatives.The numerical analysis verifies the reasonableness and effectiveness of this method.The results indicate that the new method effectively addresses the ranking issue caused by weakly equivalent alternatives,enhancing decision-making accuracy and practicality.By resolving these ambiguities,the modified TOPSIS method increases the robustness and reliability of the decision-making process.Future research could further explore the effectiveness of this method in different application scenarios and larger datasets.Additionally,integrating this method into other MCDA techniques could lead to even more precise decision-making tools.Expanding this approach could also involve investigating its applicability in real-world decision-making situations,offering deeper insights and further validation.
作者
程幼明
胡祥瑛
何惠妍
吴锋
CHENG Youming;HU Xiangying;HE Huiyan;WU Feng(College of Economics and Management,Anhui Polytechnic University,Wuhu 241000,China;College of Economics and Management,Nanjing University of Aeronautics and Astronautics,Nanjing 211100,China;Chery Automobile Co.,Ltd.,Wuhu 241006,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2024年第8期128-134,共7页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71801003)。
关键词
TOPSIS
排序方法
弱等效方案
接近度
TOPSIS
ranking method
weakly equivalent alternatives
ranking index
