Multiple-criterion decision making techniques for partner selection
In recent years, the infrastructure and logistical support for industries has improved tremendously. This has resulted in a competitive environment where suppliers can come from anywhere internationally. The Cognitive Advisor (CA) is a developed prototype which assists in selecting suitable supplier...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/17134 |
| _version_ | 1811681416132427776 |
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| author | Lau, Wei Wah. |
| author2 | Lee Siang Guan, Stephen |
| author_facet | Lee Siang Guan, Stephen Lau, Wei Wah. |
| author_sort | Lau, Wei Wah. |
| collection | NTU |
| description | In recent years, the infrastructure and logistical support for industries has improved tremendously. This has resulted in a competitive environment where suppliers can come from anywhere internationally. The Cognitive Advisor (CA) is a developed prototype which assists in selecting suitable suppliers based on contextual information and pre-determined business rules. It implements a hybrid of Analytic Hierarchy Process (AHP) and Deviation Measure techniques to rank candidate suppliers. CA is currently in its infancy status and requires a lot of beta testing. Furthermore, the results produced by the algorithms and business rules need to be validated. Therefore, in this project, the objective is to rigorously test the correctness and effectiveness of CA and provide an objective assessment of the way a suppliers’ suitability ranking is determined.
To verify the correct execution of Cognitive Advisor, sample tests were conducted. The result of CA is compared to the scores obtained by Excel spreadsheet calculation in Microsoft Office Excel 2007. To investigate the effectiveness of CA, implementation of the ranking methods were evaluated and verified 2 test scenarios. This report provides a comprehensive description on the methodology of conducting the tests and detailed analysis on the results obtained.
According to the analysis, irrelevant methods are identified. In test scenario 1, the slightly increase of payment duration from run 1 to run 8 has no significant impact on overall rankings due to low weight. In the real world scenario, capacity and payment penalty have more impact than other criteria as the application of deviation method will return highly positive (capacity) or highly negative (payment penalty) individual criterion cost. It causes rank reversal when 1 criterion performs superior and the rest performs poor and vice versa. Hence, alternative method should be researched in the future. |
| first_indexed | 2024-10-01T03:40:36Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/17134 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:40:36Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/171342023-03-04T18:56:45Z Multiple-criterion decision making techniques for partner selection Lau, Wei Wah. Lee Siang Guan, Stephen School of Mechanical and Aerospace Engineering A*STAR Singapore Institute of Manufacturing Technology Tan Puay Siew DRNTU::Engineering::Systems engineering In recent years, the infrastructure and logistical support for industries has improved tremendously. This has resulted in a competitive environment where suppliers can come from anywhere internationally. The Cognitive Advisor (CA) is a developed prototype which assists in selecting suitable suppliers based on contextual information and pre-determined business rules. It implements a hybrid of Analytic Hierarchy Process (AHP) and Deviation Measure techniques to rank candidate suppliers. CA is currently in its infancy status and requires a lot of beta testing. Furthermore, the results produced by the algorithms and business rules need to be validated. Therefore, in this project, the objective is to rigorously test the correctness and effectiveness of CA and provide an objective assessment of the way a suppliers’ suitability ranking is determined. To verify the correct execution of Cognitive Advisor, sample tests were conducted. The result of CA is compared to the scores obtained by Excel spreadsheet calculation in Microsoft Office Excel 2007. To investigate the effectiveness of CA, implementation of the ranking methods were evaluated and verified 2 test scenarios. This report provides a comprehensive description on the methodology of conducting the tests and detailed analysis on the results obtained. According to the analysis, irrelevant methods are identified. In test scenario 1, the slightly increase of payment duration from run 1 to run 8 has no significant impact on overall rankings due to low weight. In the real world scenario, capacity and payment penalty have more impact than other criteria as the application of deviation method will return highly positive (capacity) or highly negative (payment penalty) individual criterion cost. It causes rank reversal when 1 criterion performs superior and the rest performs poor and vice versa. Hence, alternative method should be researched in the future. Bachelor of Engineering (Mechanical Engineering) 2009-06-01T01:59:43Z 2009-06-01T01:59:43Z 2009 2009 Final Year Project (FYP) http://hdl.handle.net/10356/17134 en Nanyang Technological University 111 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Systems engineering Lau, Wei Wah. Multiple-criterion decision making techniques for partner selection |
| title | Multiple-criterion decision making techniques for partner selection |
| title_full | Multiple-criterion decision making techniques for partner selection |
| title_fullStr | Multiple-criterion decision making techniques for partner selection |
| title_full_unstemmed | Multiple-criterion decision making techniques for partner selection |
| title_short | Multiple-criterion decision making techniques for partner selection |
| title_sort | multiple criterion decision making techniques for partner selection |
| topic | DRNTU::Engineering::Systems engineering |
| url | http://hdl.handle.net/10356/17134 |
| work_keys_str_mv | AT lauweiwah multiplecriteriondecisionmakingtechniquesforpartnerselection |