A robust possibilistic programming approach to multiperiod hospital evacuation planning problem under uncertainty
| Autor: | Masoud Rabbani, Amir Farshbaf-Geranmayeh, Mohammad Zhalechian |
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| Rok vydání: | 2016 |
| Předmět: |
021103 operations research
Computational complexity theory Operations research Computer science Strategy and Management 0211 other engineering and technologies 02 engineering and technology Management Science and Operations Research Computer Science Applications Metaheuristic algorithms Management of Technology and Innovation 0202 electrical engineering electronic engineering information engineering Programming paradigm 020201 artificial intelligence & image processing Operations management Business and International Management Metaheuristic Sensitivity analyses Road condition |
| Zdroj: | International Transactions in Operational Research. 25:157-189 |
| ISSN: | 0969-6016 |
| DOI: | 10.1111/itor.12331 |
| Popis: | In this paper, a biobjective programming model is developed to address the hospital evacuation problem under uncertainty. It aims to concurrently minimize the total evacuation time and the total weighted number of unevacuated patients in each period. The presented model considers two types of patients and three transportation modes. Moreover, the evacuating hospitals are divided into two groups. In the first group, it is not possible to send vehicles to the evacuating hospitals due to the poor road condition or congestion, whereas there is no such limitation in the second group. A robust possibilistic programming approach is adopted to deal with the inherent uncertainty in the input data. To cope with the computational complexity of the problem, two well-known metaheuristic algorithms are developed to solve the large-sized problems. Finally, several computational experiments and sensitivity analyses are conducted and the results are analyzed. |
| Databáze: | OpenAIRE |
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