摘要
针对含机器阻塞和可利用约束的混合流水车间调度优化问题,考虑工件运输时间,以最小化总加权完工时间为优化目标,建立混合整数规划模型,提出一种基于启发式规则的自适应混合遗传算法求解该模型。在传统遗传算法的基础结构上,引入五种启发式规则生成部分初始种群,从而改善部分初始解的质量;设计分段自适应交叉概率和变异概率计算公式,以加快算法收敛;利用局域搜索对得到的调度解进行再次优化,进一步提高算法搜索能力。对不同规模问题进行仿真实验,结果验证了该算法的可行性和有效性。
Hybrid flowshop scheduling optimization is studied with blocking and vailable constraints and job transportation time,and a mixed integer programming model is formulated with the objective of minimizing total weighted completion time.The heuristic rules based self-adaptive hybrid genetic algorithm is proposed to solve this model.By means of the basic structure of traditional genetic algorithm,five heuristic rules were introduced to generate partial initial population so that quality of the initial solutions was improved.The segmented adaptive crossover probability and mutation probability were designed to enhance the convergence.Finally,the local search was applied to re-optimize the schedule to improve search ability.The simulation experiments on different sized problems show the feasibility and effectiveness of the proposed algorithm.
作者
轩华
王晶
张慧贤
李冰
Xuan Hua;Wang Jing;Zhang Huixian;Li Bing(School of Management Engineering,Zhengzhou University,Zhengzhou 450001,Henan,China)
出处
《计算机应用与软件》
北大核心
2021年第6期176-181,共6页
Computer Applications and Software
基金
国家自然科学基金项目(U1804151,U1604150)。
关键词
混合流水车间调度
机器阻塞
机器故障
自适应混合遗传算法
启发式规则
局域搜索
Hybrid flow shop scheduling
Machine blocking
Machine breakdown
Self-adaptive hybrid genetic algorithm
Heuristic rules
Local search
