An improved estimation of distribution algorithm for rescue task emergency scheduling considering stochastic deterioration of the injured
Сохранить в:
| Опубликовано в:: | Complex & Intelligent Systems vol. 10, no. 1 (Feb 2024), p. 413 |
|---|---|
| Главный автор: | |
| Другие авторы: | , , |
| Опубликовано: |
Springer Nature B.V.
|
| Предметы: | |
| Online-ссылка: | Citation/Abstract Full Text - PDF |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 2924576563 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2199-4536 | ||
| 022 | |a 2198-6053 | ||
| 024 | 7 | |a 10.1007/s40747-023-01136-x |2 doi | |
| 035 | |a 2924576563 | ||
| 045 | 2 | |b d20240201 |b d20240229 | |
| 100 | 1 | |a Xu, Ying |u Ningbo University, Faculty of Electrical Engineering and Computer Science, Ningbo, China (GRID:grid.203507.3) (ISNI:0000 0000 8950 5267); Ningbo University of Finance & Economics, College of Digital Technology and Engineer, Ningbo, China (GRID:grid.203507.3) (ISNI:0000 0000 8950 5267) | |
| 245 | 1 | |a An improved estimation of distribution algorithm for rescue task emergency scheduling considering stochastic deterioration of the injured | |
| 260 | |b Springer Nature B.V. |c Feb 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Efficient allocating and scheduling emergency rescue tasks are a primary issue for emergency management. This paper considers emergency scheduling of rescue tasks under stochastic deterioration of the injured. First, a mathematical model is established to minimize the average mathematical expectation of all tasks’ completion time and casualty loss. Second, an improved multi-objective estimation of distribution algorithm (IMEDA) is proposed to solve this problem. In the IMDEA, an effective initialization strategy is designed for obtaining a superior population. Then, three statistical models are constructed, which include two tasks existing in the same rescue team, the probability of first task being processed by a rescue team, and the adjacency between two tasks. Afterward, an improved sampling method based on referenced sequence is employed to efficiently generate offspring population. Three multi-objective local search methods are presented to improve the exploitation in promising areas around elite individuals. Furthermore, the parameter calibration and effectiveness of components of IMEDA are tested through experiments. Finally, the comprehensive comparison with state-of-the-art multi-objective algorithms demonstrates that IMEDA is a high-performing approach for the considered problem. | |
| 653 | |a Emergency management | ||
| 653 | |a Algorithms | ||
| 653 | |a Task scheduling | ||
| 653 | |a Rescue operations | ||
| 653 | |a Multiple objective analysis | ||
| 653 | |a Completion time | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Statistical models | ||
| 653 | |a Population (statistical) | ||
| 653 | |a Scheduling | ||
| 653 | |a Computer science | ||
| 653 | |a Emergency preparedness | ||
| 653 | |a Mathematical models | ||
| 653 | |a Intelligent systems | ||
| 653 | |a Optimization | ||
| 653 | |a Disasters | ||
| 653 | |a Probability distribution | ||
| 700 | 1 | |a Li, Xiaobo |u Zhejiang Normal University, School of Computer Science and Technology, Jinhua, China (GRID:grid.453534.0) (ISNI:0000 0001 2219 2654) | |
| 700 | 1 | |a Li, Qian |u Ningbo University of Finance & Economics, College of Digital Technology and Engineer, Ningbo, China (GRID:grid.203507.3) (ISNI:0000 0000 8950 5267) | |
| 700 | 1 | |a Zhang, Weipeng |u Ningbo University of Finance & Economics, College of Digital Technology and Engineer, Ningbo, China (GRID:grid.203507.3) (ISNI:0000 0000 8950 5267) | |
| 773 | 0 | |t Complex & Intelligent Systems |g vol. 10, no. 1 (Feb 2024), p. 413 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2924576563/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2924576563/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |