An efficient MILP-based algorithm for the qualitative flexible multi-criteria method under incomplete or conflicting weights

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Operations Research Pub Date : 2024-12-19 DOI:10.1016/j.cor.2024.106951
Saeed Alaei , Seyed Hossein Razavi Hajiagha , Mahnaz Hosseinzadeh
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引用次数: 0

Abstract

This study first proposes a mixed-integer linear programming model for the qualitative flexible multi-criteria method (QUALIFLEX) within an interval type-2 fuzzy environment. This extends an efficient QUALIFLEX method that already exists in the literature. The computational complexity of QUALIFLEX grows exponentially with an increase in the number of alternatives, and the extended model efficiently solves a multi-criteria decision problem and determines the best permutation regardless of the number of alternatives. A new QUALIFLEX algorithm is also developed to handle imprecise and conflicting preference structures for criteria weights. This algorithm includes both a single-objective and a bi-objective model to address incomplete and conflicting weight information, respectively, and these models are subsequently linearized. The newly developed algorithm solves the models only once to produce the best permutation and the corresponding weights, rather than requiring the solution ofm!nonlinear models as in previous studies. The implications of the proposed extended and developed algorithms are illustrated using numerical examples, and their performance is analyzed against existing methods across a set of 30 problems with varying numbers of alternatives. The formulated model achieves similar results to the previous version with a limited number of alternatives using only one model-solving attempt and demonstrates superior performance in terms of computation time for problems with a larger number of alternatives.
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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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