求解作业车间调度问题的离散海洋捕食者算法

Discrete Marine Predators Algorithm for Solving Job Shop Scheduling Problem

为把海洋捕食者算法应用于作业车间调度问题,提出了离散海洋捕食者算法。首先,对原算法的连续位置向量进行了离散转换。其次,使用对立学习方法增加初始种群的多样性;采用圆形混沌映射函数来提高算法的收敛速度;改进自适应步长策略从而更好地平衡勘探和开发。最后,通过对典型调度基准算例的测试,并同其他算法进行对比,验证了离散海洋捕食者算法在求解作业车间调度问题时的有效性及更优良的算法特性。

In order to apply the marine predator algorithm to the job shop scheduling problem,a discrete marine predators algorithm is proposed.Firstly,the continuous position vector of the original algorithm is discretely transformed.Secondly,the algorithm uses opposition based learning to increase population diversity in the population initialization stage;the algorithm uses the circle map chaotic mapping function to improve the convergence speed of the algorithm;the algorithm uses an improved adaptive step size strategy to better balance exploration and exploitation.Finally,the algorithm selects basic examples to test the performance of the algorithm,and compared with other metaheuristic algorithms,the effectiveness and superiority of discrete marine predators algorithm are verified in solving job shop scheduling problem.