装载率均衡下的集装袋库存配送优化问题

Optimization of Inventory Distribution for Flexible Container with Balanced Loading Rates

针对集装袋库存管理落后、配送车辆装载率低下的现状,研究了多周期多品种多客户的集装袋库存配送问题,以系统总成本最小和配送车辆装载率均衡性最优为双目标建立了数学模型。提出了灾变遗传退火算法求解库存策略,下层设计了C-W节约算法求解配送路径。实验结果表明,改进算法优于基本遗传算法,求得配送车辆平均装载率为83%,可为集装袋采配系统提供科学的管理决策。

In response to the challenges of outdated inventory management and low loading rates for flexible container,this paper investigates the inventory distribution problem for flexible container across multiple periods,varieties,and customers.It established a model with the dual objectives of minimizing the overall system cost and optimizing the evenness of delivery vehicle loading rates.A catastrophe genetic simulated annealing algorithm is proposed to solve the inventory strategy.A C-W savings algorithm is designed at a lower level to determine distribution routes.Experimental results demonstrate that the improved algorithm outperforms the basic genetic algorithm,achieving an average loading rate of 83%for delivery vehicles.This research provides a scientific decision for the management of the flexible container supply and distribution system.