摘要
针对多装配线流水车间调度问题,考虑遗传算法的早熟收敛特性和禁忌搜索算法具有记忆能力的局部寻优特性,将遗传算法和禁忌搜索算法进行结合,提出基于遗传算法和禁忌搜索算法的多装配线混合调度优化算法.先用遗传算法进行全局搜索,改善种群质量,再以改善后的种群作为禁忌搜索算法的初始解,进行局部搜索.依据最小化总延迟和总完工时间的调度目标,建立了一个混合整数线性规划模型,并通过实例演算验证了该混合算法求解多装配线调度问题的可行性和有效性.
In order to avoid the premature convergence and balance the exploration and exploitation abilities of simple GA, a hybrid algorithm is proposed to solve the flow shop scheduling problem of multiple assembly lines based on the flow shop scheduling problem of the multiple assembly lines. It combines the advantage of global search ability of GA with self- adaptive merit of tabu search and improves its convergence. Genetic algorithm is used for global search to improve the population quality first, and then TS algorithm is used for local search with the improved population as its initial solution. With the objective to minimize the sum of total weighted tardiness of jobs and weighted makespan, a mixed-integer linear programming model for the problem is established, and a case study is conducted to verify the usefulness and effectiveness of the hybrid algorithm for solving the scheduling problem of multiple assembly lines.
出处
《浙江工业大学学报》
CAS
2013年第4期355-359,共5页
Journal of Zhejiang University of Technology
基金
国家自然科学基金资助项目(70971118)
关键词
多装配线
遗传算法
禁忌搜索算法
调度
建模
multiple assembly lines
genetic algorithm
tabu search algorithm
scheduling
mod-eling
