A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty
In this paper, a novel multi-objective robust possibilistic programming model is proposed, which simultaneously considers maximizing the distributive justice in relief distribution, minimizing the risk of relief distribution, and minimizing the total logistics costs. To effectively cope with the unc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2016-09-01
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| Series: | International Journal of Industrial Engineering Computations |
| Subjects: | |
| Online Access: | http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_7.pdf |
| _version_ | 1818084375291494400 |
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| author | Maryam Rahafrooz Mahdi Alinaghian |
| author_facet | Maryam Rahafrooz Mahdi Alinaghian |
| author_sort | Maryam Rahafrooz |
| collection | DOAJ |
| description | In this paper, a novel multi-objective robust possibilistic programming model is proposed, which simultaneously considers maximizing the distributive justice in relief distribution, minimizing the risk of relief distribution, and minimizing the total logistics costs. To effectively cope with the uncertainties of the after-disaster environment, the uncertain parameters of the proposed model are considered in the form of fuzzy trapezoidal numbers. The proposed model not only considers relief commodities priority and demand points priority in relief distribution, but also considers the difference between the pre-disaster and post-disaster supply abilities of the suppliers. In order to solve the proposed model, the LP-metric and the improved augmented ε-constraint methods are used. Second, a set of test problems are designed to evaluate the effectiveness of the proposed robust model against its equivalent deterministic form, which reveales the capabilities of the robust model. Finally, to illustrate the performance of the proposed robust model, a seismic region of northwestern Iran (East Azerbaijan) is selected as a case study to model its relief logistics in the face of future earthquakes. This investigation indicates the usefulness of the proposed model in the field of crisis. |
| first_indexed | 2024-12-10T19:52:53Z |
| format | Article |
| id | doaj.art-5fcb2507b1674fd3946d2263415f7146 |
| institution | Directory Open Access Journal |
| issn | 1923-2926 1923-2934 |
| language | English |
| last_indexed | 2024-12-10T19:52:53Z |
| publishDate | 2016-09-01 |
| publisher | Growing Science |
| record_format | Article |
| series | International Journal of Industrial Engineering Computations |
| spelling | doaj.art-5fcb2507b1674fd3946d2263415f71462022-12-22T01:35:44ZengGrowing ScienceInternational Journal of Industrial Engineering Computations1923-29261923-29342016-09-017464967010.5267/j.ijiec.2016.3.001A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertaintyMaryam RahafroozMahdi AlinaghianIn this paper, a novel multi-objective robust possibilistic programming model is proposed, which simultaneously considers maximizing the distributive justice in relief distribution, minimizing the risk of relief distribution, and minimizing the total logistics costs. To effectively cope with the uncertainties of the after-disaster environment, the uncertain parameters of the proposed model are considered in the form of fuzzy trapezoidal numbers. The proposed model not only considers relief commodities priority and demand points priority in relief distribution, but also considers the difference between the pre-disaster and post-disaster supply abilities of the suppliers. In order to solve the proposed model, the LP-metric and the improved augmented ε-constraint methods are used. Second, a set of test problems are designed to evaluate the effectiveness of the proposed robust model against its equivalent deterministic form, which reveales the capabilities of the robust model. Finally, to illustrate the performance of the proposed robust model, a seismic region of northwestern Iran (East Azerbaijan) is selected as a case study to model its relief logistics in the face of future earthquakes. This investigation indicates the usefulness of the proposed model in the field of crisis.http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_7.pdfDisaster relief LogisticsRelief facility locationUncertaintyChance constrained possibilistic programmingRobust optimizationMulti-objective optimization |
| spellingShingle | Maryam Rahafrooz Mahdi Alinaghian A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty International Journal of Industrial Engineering Computations Disaster relief Logistics Relief facility location Uncertainty Chance constrained possibilistic programming Robust optimization Multi-objective optimization |
| title | A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| title_full | A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| title_fullStr | A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| title_full_unstemmed | A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| title_short | A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| title_sort | novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty |
| topic | Disaster relief Logistics Relief facility location Uncertainty Chance constrained possibilistic programming Robust optimization Multi-objective optimization |
| url | http://www.growingscience.com/ijiec/Vol7/IJIEC_2016_7.pdf |
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