| 资源受限下森林火灾应急救援多目标调度优化 |
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| 引用本文： | 王路兵,吴鹏,胡鹏,储诚斌,李慧嘉.资源受限下森林火灾应急救援多目标调度优化[J].运筹与管理,2023,32(1):60-66. |
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| 作者姓名： | 王路兵 吴鹏 胡鹏 储诚斌 李慧嘉 |
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| 作者单位： | 1.福州大学 经济与管理学院,福建 福州 350108; 2.北京邮电大学 理学院,北京 100876 |
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| 基金项目： | 国家自然科学基金资助项目(71871159);教育部人文社科基金一般项目(21YJA630096);福建省“雏鹰计划”青年拔尖人才项目(0470-00472214);福建省自然科学基金面上项目(2022J01075);福建省科技经济融合服务平台(0300-82321069);中国工程院院地合作项目(2021-FJ-ZD-4) |
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| 摘 要： | 许多森林火灾由于救援资源受限而不能在第一时间扑灭，导致火灾扩大蔓延，进而造成更大的森林资源损失。因此，在救援资源受限情形下，如何对消防救援车辆进行合理的调度安排以快速和低成本地扑灭火灾已成为亟待解决的现实问题。本文研究了一类资源受限下森林火灾应急救援多目标调度优化问题，为该问题构建了多目标混合整数非线性规划模型，优化目标为同时最小化总灭火救援时间和救援车辆总行驶距离。为有效求解该问题，首先将上述非线性模型等价转化为线性模型。然后提出ε-约束法和模糊逻辑相结合的算法对问题进行求解。最后，以大兴安岭山发生的火灾案例和随机生成仿真算例对模型和算法有效性进行验证，结果表明所提出的模型和算法能够有效解决资源受限下森林火灾应急救援问题，并为决策者提供最优的消防调度方案。
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| 关 键 词： | 森林火灾 资源受限 应急救援 多目标优化 ε-约束法 |
| 收稿时间： | 2020-11-29 |
Multi-objective Optimization for Forest Fires Emergency Rescue Scheduling with Resource Constraints |
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| WANG Lubing,WU Peng,HU Peng,CHU Chengbin,LI Huijia.Multi-objective Optimization for Forest Fires Emergency Rescue Scheduling with Resource Constraints[J].Operations Research and Management Science,2023,32(1):60-66. |
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| Authors: | WANG Lubing WU Peng HU Peng CHU Chengbin LI Huijia |
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| Affiliation: | 1. School of Economics and Management, Fuzhou University, Fuzhou 350108, China; 2. School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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| Abstract: | Many forest fire disasters cannot be extinguished in a short time due to limited emergency rescue resources, leading to the spread of fire and the loss of forest resources. Therefore, how to reasonably dispatch fire-fighting rescue vehicles to efficiently extinguish fire points at a low cost has become a practical problem. For this problem, this paper instigates a novel multi-objective forest fires emergency scheduling problem subject to limited rescue resources. First, we develop a mixed-integer nonlinear programming model to minimize the total extinguishing rescue time and the total travel distance of the rescue vehicles, simultaneously. To efficiently solve it, the nonlinear model is then transformed into an equivalent linear model. Then, we propose an ε-constraint and fuzzy-logic combined method to solve the linear model, in which the ε-constraint method obtains the Pareto front and the fuzzy-logic method recommend a preferred Pareto-optimal solution. Finally, numerical experiments on a real forest fire case in Daxing’anling, China and randomly-generated instances are conducted to verify the effectiveness of the proposed model and algorithm. The computational results show that our proposed model and algorithm can effectively solve the multi-objective forest fires emergency rescue scheduling problem under resource constraints, and provide decision-makers with the most preferred emergency scheduling scheme. |
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| Keywords: | forest fires resource constraints emergency rescue multi-objective optimization ε-constraint |
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