基于动态学习和个体淘汰的鲸鱼算法求解订单接受与调度问题

结合订单型企业生产线的实际情况,在传统的订单接受与调度模型的基础上加入因客户优先级而带来的订单拒绝成本这一重要因素,并使用新型的鲸鱼优化算法(WOA)进行求解.WOA被提出是用于求解实数域的问题而且存在容易陷入局部最优的缺陷,针对这一问题提出一种改进的鲸鱼优化算法(IWOA).使用基于排序和偏离度的编码方式用于求解订单...

Whale Optimization Algorithm Based on Dynamic Learning and Individual Elimination Strategy to Solve Order Acceptance and Scheduling Problems

Combined with the actual situation of the production line of order-oriented enterprises, the important factor of order rejection cost due to customer priority was added to the traditional order acceptance model, and the new whale optimization algorithm (WOA) was used to solve the problem. WOA was proposed to solve real number domain problems and had the defect of easily falling into local optimum. To solve this problem, an improved whale optimization algorithm (IWOA) was proposed. The coding method based on ranking and deviation degree was used to solve the integer domain problem of the order acceptance model. Adding a dynamic learning strategy from historical individuals could avoid premature algorithms to a certain extent. In order to prevent whale individuals from deviating from the optimal direction in the process of random search and thus affecting the convergence speed, the cross-selection strategy of genetic algorithm was used to eliminate inferior individuals. The experiment compares IWOA with WOA and the improved gray wolf algorithm (HGWO), which proves the advantages of IWOA in solving the order acceptance model, the stability of result, the convergence speed of the algorithm itself and the quality of initial solution, etc.