Joint Optimization of Emergency Resource Scheduling for Forest Fires Considering Road Obstruction

doi:10.3969/j.issn.1007-7375.230136

Abstract

Abstract: A new joint optimization problem for emergency resource scheduling is studied to address the possible obstruction issue of transportation roads after forest fires. A mixed-integer linear programming model for joint scheduling of emergency resources for forest fires is established considering both resource constraints and road obstruction. The optimization objective is to minimize the fire rescue time to reduce the resource loss caused by forest fires. To quickly and efficiently solve the problem, an improved artificial bee colony algorithm with two encoding methods is designed according to the problem characteristics. Finally, experimental results from typical instances and stochastic simulation instances show that i) for real-life instances and small- to medium-scale simulation instances, the optimal fire rescue plan can be obtained within 5 minutes by using the commercial solver CPLEX; and ii) for large-scale forest fires, the proposed improved artificial bee colony algorithm outperforms the commercial solver CPLEX, achieving a higher-quality fire rescue plan in just 10 seconds. It can provide an effective fire rescue plan for emergency teams with road obstruction.

Key words: forest fires, road obstruction, joint scheduling, linear programming, artificial bee colony algorithm

CLC Number:

S762.3
F406

WU Peng, WANG Lubing, CHU Chengbin. Joint Optimization of Emergency Resource Scheduling for Forest Fires Considering Road Obstruction[J]. Industrial Engineering Journal, 2024, 27(4): 121-131.

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