基于改进AOA的联合采购与配送问题研究

Research on Enhanced Arithmetic Optimization Algorithm for Joint Replenishment and Delivery Problem

针对算术优化算法(AOA)个体信息利用率较低和容易陷入局部最优的缺点,采用信息交换策略并结合正余弦(SCA)算法,设计了基于SCA的改进算术优化算法(EAOA),以提高AOA算法的寻优能力。采用标准测试函数测试EAOA的性能,结果表明EAOA比遗传算法、差分进化算法和标准AOA更有效。针对大规模联合采购与配送协同优化问题的求解,EAOA比遗传算法、差分进化算法和标准AOA得到的总成本更低。

The individual information utilization rate of arithmetic optimization algorithm(AOA)is low and AOA is easy to fall into local optimal.This study used information exchange strategy and combined sine cosine algorithm(SCA),designed an enhanced arithmetic optimization algorithm(Enhanced AOA,EAOA)based on SCA to improve the ability of the AOA algorithm.The standard benchmark functions were used to test the performance of EAOA.The results show that the designed EAOA is more effective than the genetic algorithm,differential evolution algorithm,and standard arithmetic optimization algorithm.To solve large-scale joint replenishment and delivery problems,EAOA obtained a lower total cost than genetic algorithm,differential evolution algorithm,and standard arithmetic optimization algorithm.