Abstract: In order to satisfy the demands of supply chain logistics, considering with multi-type vehicles, capacity of the vehicle, fuel consumption of the vehicle, maximum delivery distance of vehicle, and aiming to minimize the fuel consumption and delivery distance, the paper constructs a model of Multi-Type Vehicle Routing Problem in Supply Chain（MTVRPSC） and proposes a chaotic fireworks algorithm to solve it. The proposed algorithm takes the fireworks algorithm as the core, and proposes a codec strategy to accomplish a mapping from the continuous space to the discrete space of MTVRPSC, and redefines the fitness function, fitness value and comparative approach of fitness. The proposed algorithm also adopts the chaotic initialization strategy and chaotic search strategy to enhance the convergent effect. Experimental results show that, the proposed algorithm has the strong optimization ability and stability to solve MTVRPSC.

Key words: fireworks algorithm, chaotic optimization algorithm, supply chain, vehicle routing problem

摘要： 为了满足供应链物流的不同需求，考虑多种车型、车辆容量、车辆油耗、车辆最大配送距离等约束条件，以最小油耗、最短配送距离为目标，建立多车型供应链物流运输调度模型（Multi-Type Vehicle Routing Problem in Supply Chain，MTVRPSC），并提出一种混沌烟花算法求解该模型。该算法以烟花算法为核心，提出一种编解码策略实现连续空间到MTVRPSC离散空间的映射，重新定义算法的适应度函数、适应度值和适应度的比较方法，并采用混沌初始化策略和混沌搜索策略来增强算法收敛效果。实验结果表明，所提出的算法在求解MTVRPSC时具有较强的寻优能力和稳定性。

关键词: 烟花算法, 混沌优化算法, 供应链, 车辆路径问题