Name
Abstract | ||
|---|---|---|
Suitable site selection for a specific purpose is a crucial activity, and of the greatest importance to a project manager. Several methods have been proposed by the research community for effective site selection, but all proposed methods incur high costs. This study explores the combination of a rough set theory approach (RSTA) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for suitable site selection for food distribution. This method provides a set of rules to determine different sites, which ultimately can help management develop strategies for suitable site selection. A set of rules for suitable site selection are derived from information related to a practical case, Pakistan Red Crescent Society (PRCS), to demonstrate the prediction ability of RSTA. The results clearly demonstrate that the RSTA model can be a valuable tool for site identification. Rough set theory also assists management in making appropriate decisions based on their objectives while avoiding unnecessary costs. However, while RSTA provides rules to determine the best sites for food distribution, it does not pinpoint the best sites for food distribution. To be more precise and accurate, this work is extended to another multi-criteria decision-making technique solution: the TOPSIS method. By using this method, this study provides the best top priority site for food distribution of PRCS. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.3233/IFS-151941 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Site selection,rough set theory,TOPSIS,multi-criteria decision making (MCDM) | Red Crescent,Data mining,Food distribution,Ideal solution,Operations research,Rough set,Site selection,Project manager,TOPSIS,Mathematics | Journal |
Volume | Issue | ISSN |
29 | 6 | 1064-1246 |
Citations | PageRank | References |
3 | 0.37 | 3 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changez Khan | 1 | 16 | 1.86 |
| Sajid Anwar | 2 | 184 | 19.96 |
| Shariq Bashir | 3 | 3 | 0.37 |
| Abdul Rauf | 4 | 30 | 5.37 |
| Adnan Amin | 5 | 42 | 6.27 |