摘要
考虑将电动车辆用来进行基于点对点配送策略的汽车装配线的物料配送,提出了改进多目标布谷鸟搜索算法.首先,对该物料配送调度问题进行描述,在统筹考虑电量限制和准时化配送要求的基础上建立了以车辆数量和最长搬运时间作为衡量指标的目标函数,并开发了直接反映配送车辆和配送次序的融合编码机制.然后,设计任务分配规则构造初始解,并在基于混沌动态步长的搜索过程中加入高斯变异和精英选择策略来提高算法的全局搜索能力和解的质量.此外,开发两种局部搜索算子以强化算法深度寻优能力.最后,仿真实验结果验证了该调度算法的可行性和有效性.
Considering employing the electric vehicles to deliver parts to stations for assembly lines based on point-to-point delivery strategy,an improved multi-objective cuckoo search algorithm is presented.First,the scheduling problem of material delivery is formally described,and the number of electric vehicles and the maximum handling time are selected as the components of the objective function based on overall consideration of power limit and on-time delivery requirements.After that,a fusion encoding mechanism reflecting directly the vehicle and sequence of the delivery is put forward in the algorithm.Then,a task allocation rule is designed to generate the initial solutions,and Gaussian mutation and elite selection strategy are incorporated into the search process based on chaotic dynamic step size to improve global search ability of the algorithm as well as the quality of the solutions.Furthermore,two local search operators are proposed to enhance the algorithm′s ability for deep optimization.Finally,the simulation results verify the feasibility and effectiveness of the proposed scheduling algorithm.
作者
周炳海
李秀娟
ZHOU Binghai;LI Xiujuan(School of Mechanical and Energy Engineering,Tongji University,Shanghai 201804,China)
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2020年第12期1-8,共8页
Journal of Hunan University:Natural Sciences
基金
国家自然科学基金资助项目(71471135)。
关键词
点对点物料配送
电动车辆
多目标优化
布谷鸟搜索
point-to-point material delivery
electric vehicle
multi-objective optimization
cuckoo search
