解优先级约束并行机调度问题的人工免疫算法

Artificial immune algorithm for solving priority constraint scheduling problem on parallel machines

针对家纺企业车间调度的实际情况,建立了优先级特殊工艺约束下并行多机拖后调度模型,并提出一种新颖的人工免疫算法对其求解。该算法是依据生物的免疫机理,将目标函数作为抗原,将问题的解作为抗体,对抗体采用向量组编码的方式进行编码,通过克隆、变异及一种新颖的基于浓度的种群多样性更新选择方法,提高了种群多样性,并通过局部搜索改善了种群质量,加快了收敛速度。仿真结果表明,与遗传算法相比较,该算法能更快更准确地收敛到全局最优解。

According to the practical job-shop scheduling problem in textile manufacturing industry,a multi-machine tardiness scheduling model subjected to priority constraint is constructed,and thus a novel artifical immune algorithm based on immune system（VIA） is proposed to solve it.In the proposed algorithm,the antigens and anbodies correspond to the objective functions and solutions of scheduling problems,respectively.The vector group encoding method is adopted,and a new diversity selection scheme is designed to guarantee the diversity of the popultion.Specially,a local search algorithm is presented to improve the quality of the population.Simulation results show that VIA is efficient,and has better convergence than genetic algorithms.