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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

Selection of optimum plant layout using AHP-TOPSIS and WASPAS approaches coupled with Entropy method Pages 545-562 Right click to download the paper Download PDF

Authors: Anand S. Shivade, Sagar U. Sapkal

DOI: 10.5267/j.dsl.2022.5.002

Keywords: Unequal area plant layout, MCDM, AHP, TOPSIS, WASPAS, Entropy method, Rank Reversal

Abstract:
Layout design and selection often have notable effects on the performance of the manufacturing industry. This research investigates the Multi-Criteria Decision Making (MCDM) approach to find out the optimum plant layout design. The proposed methodology is demonstrated through the real-life setting for the gearbox manufacturing industry. Manual and computerized layout generation approach is used efficiently and accordingly, six layout designs are generated. The approach takes into account qualitative as well as quantitative performance criteria for the selection of layout design. Analytical Hierarchy Process (AHP) is applied to obtain the weight of qualitative measures. Ranking of alternatives is obtained through the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum-Product Assessment (WASPAS) both integrated with the Entropy method. Empirical findings indicate that the rank acquired using the TOPSIS method is perfectly parallel to those acquired through the WASPAS method, which confirms the applicability and potential of these methods. Also, the effect of the parameter λ in WASPAS method on performance score is stable. At the same time, this paper analyses the rank reversal phenomenon and proves that the ranking proposed by TOPSIS satisfies ranking stability.
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Journal: DSL | Year: 2022 | Volume: 11 | Issue: 4 | Views: 1297 | Reviews: 0

 
2.

The selection of the best olympic place for Turkey using an integrated MCDM model Pages 1-16 Right click to download the paper Download PDF

Authors: Coşkun Karaca, Alptekin Ulutaş, Gül Yamaner, Ayşe Topal

DOI: 10.5267/j.dsl.2018.5.005

Keywords: Selection of Olympic Games Place, Entropy Method, COPRAS method

Abstract:
Hosting Olympic Games is a significant opportunity for every country and her metropolitan cities. Olympics offer several benefits to the Host countries and cities such as introducing cultural assets of the country to the world and increasing economic value of the country and city Olympics held. Countries and cities wishing to host Olympic Games have to prove that they have the qualifications to be host of these games. The International Olympic Committee (IOC) has identified 5 main criteria and 22 sub-criteria to determine the objectivity measure of this adequacy. These criteria are in conflict with each other so multi-criteria decision making (MCDM) methods can be useful to determine the best host country and its city for Olympic Games. In this study, an integrated MCDM model is proposed to determine the best metropolitan city in Turkey for hosting of the Olympic Games. The contribution of this study is that there are very few studies related to the selection of hosting places for Olympic Games using MCDM methods. The results of the integrated model show that Antalya is the best metropolitan host for Olympic Games.
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Journal: DSL | Year: 2019 | Volume: 8 | Issue: 1 | Views: 2537 | Reviews: 0

 
3.

A novel method to extend SAW for decision-making problems with interval data Pages 225-236 Right click to download the paper Download PDF

Authors: Alireza Salehi, Mohammad Izadikhah

Keywords: Entropy method, Interval data, Multiple Criteria Decision-Making, SAW method

Abstract:
Decision making problem is the process of finding the best option out of all feasible alternatives. There are some methods for solving Multiple Criteria Decision-Making problems and Simple Additive Weighting (SAW) is one of the most popular ones. In this paper, among multi-criteria models in making complex decisions and multiple attribute models for the most preferable choice, SAW technique is extended using interval numbers. For this purpose, we first propose a method for extending Entropy method for dealing with interval data, and then the extended SAW method with interval data is proposed by using the interval weights derived by the proposed interval Entropy method. The extended SAW method is an algorithm to determine the most preferable choice out of all possible choices, when the input data are stated in interval.
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Journal: DSL | Year: 2014 | Volume: 3 | Issue: 2 | Views: 3819 | Reviews: 0

 

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