期刊名称：International Journal of Industrial Engineering Computations
印刷版ISSN：1923-2926
电子版ISSN：1923-2934
出版年度：2011
卷号：2
期号：2
页码：369-384
DOI：10.5267/j.ijiec.2010.07.002
语种：English
出版社：Growing Science Publishing Company
摘要：The permutation method of multiple attribute decision making has two significant deficiencies:high computational time and wrong priority output in some problem instances. In this paper, anovel permutation method called adjusted permutation method (APM) is proposed tocompensate deficiencies of conventional permutation method. We propose Tabu search (TS)and particle swarm optimization (PSO) to find suitable solutions at a reasonable computationaltime for large problem instances. The proposed method is examined using some numericalexamples to evaluate the performance of the proposed method. The preliminary results showthat both approaches provide competent solutions in relatively reasonable amounts of timewhile TS performs better to solve APM.
