A study on the ranking performance of some MCDM methods for industrial robot selection problems
In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of r...
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| Format: | Article |
| Language: | English |
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Growing Science
2016-06-01
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| Series: | International Journal of Industrial Engineering Computations |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_1.pdf |
| _version_ | 1819149495289511936 |
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| author | Prasad Karande Edmundas Kazimieras Zavadskas Shankar Chakraborty |
| author_facet | Prasad Karande Edmundas Kazimieras Zavadskas Shankar Chakraborty |
| author_sort | Prasad Karande |
| collection | DOAJ |
| description | In this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria. |
| first_indexed | 2024-12-22T14:02:31Z |
| format | Article |
| id | doaj.art-a04cee294b504ad1bea5aacfcd16761c |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-12-22T14:02:31Z |
| publishDate | 2016-06-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-a04cee294b504ad1bea5aacfcd16761c2022-12-21T18:23:23ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342016-06-017339942210.5267/j.ijiec.2016.1.001A study on the ranking performance of some MCDM methods for industrial robot selection problemsPrasad KarandeEdmundas Kazimieras ZavadskasShankar ChakrabortyIn this paper, the ranking performance of six most popular and easily comprehensive multi-criteria decision-making (MCDM) methods, i.e. weighted sum method (WSM), weighted product method (WPM), weighted aggregated sum product assessment (WASPAS) method, multi-objective optimization on the basis of ratio analysis and reference point approach (MOORA) method, and multiplicative form of MOORA method (MULTIMOORA) is investigated using two real time industrial robot selection problems. Both single dimensional and high dimensional weight sensitivity analyses are performed to study the effects of weight variations of the most important as well as the most critical criterion on the ranking stability of all the six considered MCDM methods. The identified local weight stability interval indicates the range of weights within which the rank of the best alternative remains unaltered, whereas, the global weight stability interval determines the range of weights within which the overall rank order of all the alternatives remains unaffected. It is observed that for both the problems, multiplicative form of MOORA is the most robust method being least affected by the changing weights of the most important and the most critical criteria.http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_1.pdfMCDMWSMWPMWASPASMOORAReference point approachMULTIMOORAIndustrial robot selectionRankSensitivity analysis |
| spellingShingle | Prasad Karande Edmundas Kazimieras Zavadskas Shankar Chakraborty A study on the ranking performance of some MCDM methods for industrial robot selection problems International Journal of Industrial Engineering Computations MCDM WSM WPM WASPAS MOORA Reference point approach MULTIMOORA Industrial robot selection Rank Sensitivity analysis |
| title | A study on the ranking performance of some MCDM methods for industrial robot selection problems |
| title_full | A study on the ranking performance of some MCDM methods for industrial robot selection problems |
| title_fullStr | A study on the ranking performance of some MCDM methods for industrial robot selection problems |
| title_full_unstemmed | A study on the ranking performance of some MCDM methods for industrial robot selection problems |
| title_short | A study on the ranking performance of some MCDM methods for industrial robot selection problems |
| title_sort | study on the ranking performance of some mcdm methods for industrial robot selection problems |
| topic | MCDM WSM WPM WASPAS MOORA Reference point approach MULTIMOORA Industrial robot selection Rank Sensitivity analysis |
| url | http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_1.pdf |
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