基于Cell-DEVS的森林灭火资源调度狼群优化算法

针对森林消防调度兵力组织难、精细化程度不高的问题，提出了一种基于Cell-DEVS的森林灭火资源调度狼群优化算法。首先，利用Rothermel林火蔓延模型，对林火蔓延速度进行等级划分；其次，根据森林消防"控制要害"的原则，对森林灭火资源调度进行耦合驱动模块化建模，建立了基于Cell-DEVS模型的狼群强者生存更新机制（WSSUM）；最后，针对森林灭火资源在单位时间步长局部调度搜索中不够精细的问题，提出了一种改进局部搜索策略狼群优化算法（WOA），对资源在局部游走阶段实现调度交互。与WSSUM算法相比，WOA在减少任务执行时间的同时，改善了局部搜索性能，实验结果表明：收敛速度较改进前提高了10.1%。该研究适应于配备了定位设备的单兵消防作战指挥系统，实现差异化精细调兵。

Wolves optimization algorithm based on Cell-DEVS for forest fire-fighting resource scheduling

In view of the difficulty of forest fire-fighting dispatching force organization and low degree of refinement,a wolves optimization algorithm based on Cell-DEVS(Discrete Event System Specification) for forest fire-fighting resource scheduling was proposed. Firstly, Rothermel forest fire spread model was used to classify forest fire spread rate. Secondly, according to the principle of control the key in forest fire control, the forest fire-fighting resource scheduling model was built by a way of coupling drive modular designing,and a Wolves Strong Survival Update Mechanism (WSSUM) based on the Cell-DEVS model was proposed. Finally, aiming at the problem that the scheduling of forest fire-fighting resources was not fine enough in the local search of unit time step, an modified Wolves Optimization Algorithm (WOA) based on improved local search strategy was adopted to schedule the forest fire fighting resources in the local walk interactively. In the comparison experiments with WSSUM algorithm, the WOA improved the local search performance while reducing the task execution time. The experimental results show that the convergence speed is improved by 10.1% compared with that before improvement. The study adapts to the individual fire-fighting command system equipped with locating equipment to realize differentiated fine force dispatching.