Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem
Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant si...
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| Format: | Article |
| Language: | English |
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Islamic Azad University, Qazvin Branch
2019-07-01
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| Series: | Journal of Optimization in Industrial Engineering |
| Subjects: | |
| Online Access: | http://www.qjie.ir/article_270_c7bb886bf28f827788f5af2443b6c4f5.pdf |
| _version_ | 1818409156731731968 |
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| author | Seyed Meysam Mousavi Hossein Gitinavard Behnam Vahdani Nazanin Foroozesh |
| author_facet | Seyed Meysam Mousavi Hossein Gitinavard Behnam Vahdani Nazanin Foroozesh |
| author_sort | Seyed Meysam Mousavi |
| collection | DOAJ |
| description | Proposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromise ranking is more capable and powerful than the classical compromise ranking. This research extends a new hierarchical group compromise ranking methodology under a hesitant fuzzy (HF)environment to handle uncertainty, in which for the margin of error, the DMs could assign the opinions in several membership degrees for an element. The hesitant fuzzy set (HFS)is taken into account for the process of the proposed hierarchical group compromise ranking methodology, namely HFHG-CR, and for avoiding the data loss, the DMs’ opinions with risk preferences are considered for each step separately. Also, the Euclidean–Hausdorff distance measure is utilized in a new proposed index for calculating the average group score, worst group score and compromise measure regarding each DM. A new ranking index is presented for final compromise solution for the evaluation. Proposed HFHG-CR methodology is applied to a practical example for a facility location selection problem, i.e. cross-dock location problem, to show the validation and application. |
| first_indexed | 2024-12-14T09:55:09Z |
| format | Article |
| id | doaj.art-4fee317a65834be480617aaa01399521 |
| institution | Directory Open Access Journal |
| issn | 2251-9904 2423-3935 |
| language | English |
| last_indexed | 2024-12-14T09:55:09Z |
| publishDate | 2019-07-01 |
| publisher | Islamic Azad University, Qazvin Branch |
| record_format | Article |
| series | Journal of Optimization in Industrial Engineering |
| spelling | doaj.art-4fee317a65834be480617aaa013995212022-12-21T23:07:24ZengIslamic Azad University, Qazvin BranchJournal of Optimization in Industrial Engineering2251-99042423-39352019-07-011229310510.22094/joie.2016.270270Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection ProblemSeyed Meysam Mousavi0Hossein Gitinavard1Behnam Vahdani2Nazanin Foroozesh3Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, IranDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, IranDepartment of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranDepartment of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, IranProposing a hierarchical group compromise method can be regarded as a one of major multi-attributes decision-making tool that can be introduced to rank the possible alternatives among conflict criteria. Decision makers’ (DMs’) judgments are considered as imprecise or fuzzy in complex and hesitant situations. In the group decision making, an aggregation of DMs’ judgments and fuzzy group compromise ranking is more capable and powerful than the classical compromise ranking. This research extends a new hierarchical group compromise ranking methodology under a hesitant fuzzy (HF)environment to handle uncertainty, in which for the margin of error, the DMs could assign the opinions in several membership degrees for an element. The hesitant fuzzy set (HFS)is taken into account for the process of the proposed hierarchical group compromise ranking methodology, namely HFHG-CR, and for avoiding the data loss, the DMs’ opinions with risk preferences are considered for each step separately. Also, the Euclidean–Hausdorff distance measure is utilized in a new proposed index for calculating the average group score, worst group score and compromise measure regarding each DM. A new ranking index is presented for final compromise solution for the evaluation. Proposed HFHG-CR methodology is applied to a practical example for a facility location selection problem, i.e. cross-dock location problem, to show the validation and application.http://www.qjie.ir/article_270_c7bb886bf28f827788f5af2443b6c4f5.pdfCompromise rankingGroup decision-makingLast aggregationEuclidean–Hausdorff distance measureHesitant fuzzy setsFacility location selection problem |
| spellingShingle | Seyed Meysam Mousavi Hossein Gitinavard Behnam Vahdani Nazanin Foroozesh Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem Journal of Optimization in Industrial Engineering Compromise ranking Group decision-making Last aggregation Euclidean–Hausdorff distance measure Hesitant fuzzy sets Facility location selection problem |
| title | Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem |
| title_full | Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem |
| title_fullStr | Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem |
| title_full_unstemmed | Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem |
| title_short | Hierarchical Group Compromise Ranking Methodology Based on Euclidean–Hausdorff Distance Measure Under Uncertainty: An Application to Facility Location Selection Problem |
| title_sort | hierarchical group compromise ranking methodology based on euclidean hausdorff distance measure under uncertainty an application to facility location selection problem |
| topic | Compromise ranking Group decision-making Last aggregation Euclidean–Hausdorff distance measure Hesitant fuzzy sets Facility location selection problem |
| url | http://www.qjie.ir/article_270_c7bb886bf28f827788f5af2443b6c4f5.pdf |
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