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• W3113287032 endingPage "106936" @default.
• W3113287032 startingPage "106936" @default.
• W3113287032 abstract "In any multi-criteria decision making (MCDM) process, the role of criteria weights is highly critical, as any inconsistency associated with their weights prompts an off-base assessment and leads to non-optimal selections. In this work, a novel subjective method for determining optimal criteria weights is presented, in which a newly proposed measure of inconsistency termed as ‘Error Index’ is used to formulate a non-linear constrained optimization model. The model was solved using Particle Swarm Optimization (PSO) technique, due to its faster convergence and simpler computation as compared to Genetic Algorithm, Ant Colony and, Firefly optimization methods. For the sake of simulation, a user-friendly solver named ‘Criteria Weight Estimation using Non-Linear Programming (CWENLiP)’ is also developed. Since the error index incorporates both the global and the local characteristics of the inconsistent matrix, it is more indicative of the overall inconsistency present in the comparison matrix, in contrast with the frequently employed consistency ratio index. Several numerical problems were solved to illustrate the procedure and to explore the potential applications of the proposed method. The robustness check, the statistical significance test and, the comparative analysis were also performed. The results revealed that the proposed method is highly robust and efficient. Hence, the Error Index based inconsistency quantification, combined with user-friendly CWENLiP solver, is a more reliable tool for criteria weight estimation which is crucial for accurate ranking and improved decision making, especially for problems encompassing large sets of criteria." @default.
• W3113287032 created "2020-12-21" @default.
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• W3113287032 date "2021-03-01" @default.
• W3113287032 modified "2023-10-14" @default.
• W3113287032 title "Towards minimization of overall inconsistency involved in criteria weights for improved decision making" @default.
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• W3113287032 doi "https://doi.org/10.1016/j.asoc.2020.106936" @default.
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