基于IVNS-ASPSO算法激增需求下第四方物流网络设计

The Fourth Party Logistics Network Design with Surging Demand Based on IVNS-ASPSO Algorithm

近年来各大电商平台的不定期优惠活动导致需求激增的现象出现,激增需求下的网络设计问题成为了第四方物流(4PL)运作模式下一个新的挑战性问题。针对这一问题,基于对激增需求的刻画,建立了激增需求下4PL网络设计的数学模型。由于该问题的NPhard特性,采用自适应策略粒子群算法进行求解。并针对粒子群算法后期局部搜索能力不足,提出了迭代变邻域搜索策略,进而提出了嵌入迭代变邻域搜索的自适应策略粒子群算法,最后采用三组不同规模的算例进行仿真实验,验证了所提算法的有效性和优越性。

In recent years, the irregular preferential activities of major e-commerce platforms have led to the emergence of surging demand. Under the operation mode of the fourth party logistics(4 PL), the network design problem under the surging demand has become a new challenging problem. Aiming at this problem, the mathematical model of 4 PL network design is established based on the description of surging demand. Because of the NP-hard characteristic, the adaptive strategy particle swarm optimization algorithm is adopted to solve it.In view of the shortage of local search ability in the later stage of particle swarm optimization algorithm, the strategy of iterative variable neighborhood search is proposed in this paper, and then the iterative variable neighborhood search-adaptive strategy particle swarm optimization algorithm is proposed. Finally, three groups of examples with different scales are simulated to verify the effectiveness and superiority of the proposed algorithm.