基于混沌蚁群算法的应急救援车辆调度优化

Vehicle scheduling optimization based on chaos ant colony system algorithm in emergency rescue

针对应急救援车辆调度优化问题的特征和需求,以可变双向距离、道路风险和成本最小为主要目标,建立了应急救援车辆调度优化问题的多目标优化模型。为避免过早陷入局部最优,提出了基于混沌扰动的改进蚁群系统优化算法。该算法可对信息素进行全局更新混沌扰动,有效地提高了算法的适应性、求解效率和求解质量。仿真实验表明该算法是可行的,能较好地满足应急救援车辆调度的优化需求。

According to demand and characteristics of vehicle scheduling in emergency rescue, this paper established a multi- objective optimization model, which treated variable directed distance, path cost and path risk as the optimization target. To avoid the remaining local optima of the ant colony system （ACS） algorithm, and in order to improve algorithm adaptability, com- putational efficiency and solution quality of the optimal solution,it proposed and realized a chaos-based ant colony system algo- rithm. Simulation results show that the algorithm is feasible, can well meet the demand of vehicle scheduling optimization in emergency rescue.