改进SHO求解自动化立体仓库能耗优化调度问题  

Improved SHO for Energy-Optimized Task Scheduling of Automated Warehouse

作　　者：刘凯 吉卫喜 LIU Kai;JI Weixi(School of Mechanical Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China)

机构地区：[1]江南大学机械工程学院,江苏无锡214122

出　　处：《计算机工程与应用》2024年第16期302-310,共9页Computer Engineering and Applications

基　　金：山东省重大科技创新工程基金(2019JZZY020111)。

摘　　要：针对带有完工时间约束的自动化立体仓库任务调度问题,提出一种货位再分配策略,对货物进行合理的货位分配,并产生任务先后约束,建立以堆垛机总能耗最低为优化目标的数学调度模型,并引入相应的惩罚函数,采用一种改进的海马优化算法(improved sea-horse optimizer,I-SHO)作为全局优化算法并进行求解。在原始海马优化算法(sea-horse optimizer,SHO)的基础上,融合混沌映射与对立学习策略,提高了初始解的质量。引入自适应t分布变异策略,避免陷入局部最优,并且设置修正机制,使解满足任务先后约束。引入混合种群寻优策略,进一步优化算法的搜索能力。最后通过实验进行验证,将海马优化算法、遗传算法(genetic algorithm,GA)和粒子群算法(particle swarm optimization,PSO)作为对比算法,验证了I-SHO在求解自动化立体仓库能耗优化调度问题上的有效性。Aiming at the task scheduling problem in automated warehouse with completion time constraint,a bin reassignment strategy is proposed to allocate goods to reasonable bins and generate task sequence constraints.A mathematical scheduling model is established with the objective of minimizing the total energy consumption of the stacker crane,and a corresponding penalty function is introduced.An improved sea-horse optimizer(I-SHO)algorithm is employed as the global optimization algorithm to solve this problem.Based on the sea-horse optimizer(SHO),the chaotic Tent mapping and opposition-based learning strategy are integrated to improve the quality of initial solutions while ensuring the ergodic uniformity.An adaptive t-distribution mutation strategy is introduced to increase population quality and prevent convergence to local optima in the algorithm.Besides,a correction mechanism is set up to ensure that solutions meet task sequence constraints.A hybrid population optimization strategy is introduced to further improve population quality and search accuracy.Finally,through the verification of examples,the sea-horse optimizer,genetic algorithm(GA),and particle swarm optimization(PSO)are used as comparison algorithms,and the feasibility and effectiveness of the I-SHO algorithm in solving the energy optimization scheduling problem of automated warehouse are verified.

关 键 词：任务调度优化 能耗优化 修正机制 改进海马优化算法 

分 类 号：TP315[自动化与计算机技术—计算机软件与理论]