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Main Authors: Ratandhara, Harshit, Kumar, Mohit
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2408.14452
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author Ratandhara, Harshit
Kumar, Mohit
author_facet Ratandhara, Harshit
Kumar, Mohit
contents The Best-Worst Method (BWM) is a well-known distance based multi-criteria decision-making method used for computing the weights of decision criteria. This article examines a taxicab distance based model of the BWM, with the objective of developing a framework for deriving the model's optimal weights by solving its associated optimization problem analytically. To achieve this, an optimal modification based optimization problem, equivalent to the original one, is first formulated. This reformulated problem is then solved analytically, and the optimal weight sets are derived from its solutions. Contrary to existing literature that asserts the uniqueness of optimal weight sets based on numerical examples, our findings reveal that, in some cases, the taxicab BWM leads to multiple optimal weight sets. A mixed-integer linear programming model is then employed to compute the consistency index. This framework provides a solid mathematical foundation that enhances understanding of the model. It also eliminates the requirement for optimization software, improving the model's precision and efficiency. Finally, the effectiveness of the proposed framework is demonstrated through numerical examples.
format Preprint
id arxiv_https___arxiv_org_abs_2408_14452
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Taxicab distance based best-worst method for multi-criteria decision-making: An analytical approach
Ratandhara, Harshit
Kumar, Mohit
Optimization and Control
The Best-Worst Method (BWM) is a well-known distance based multi-criteria decision-making method used for computing the weights of decision criteria. This article examines a taxicab distance based model of the BWM, with the objective of developing a framework for deriving the model's optimal weights by solving its associated optimization problem analytically. To achieve this, an optimal modification based optimization problem, equivalent to the original one, is first formulated. This reformulated problem is then solved analytically, and the optimal weight sets are derived from its solutions. Contrary to existing literature that asserts the uniqueness of optimal weight sets based on numerical examples, our findings reveal that, in some cases, the taxicab BWM leads to multiple optimal weight sets. A mixed-integer linear programming model is then employed to compute the consistency index. This framework provides a solid mathematical foundation that enhances understanding of the model. It also eliminates the requirement for optimization software, improving the model's precision and efficiency. Finally, the effectiveness of the proposed framework is demonstrated through numerical examples.
title Taxicab distance based best-worst method for multi-criteria decision-making: An analytical approach
topic Optimization and Control
url https://arxiv.org/abs/2408.14452