Research on dynamic flexible job shop scheduling based on improved crow search algorithm
Workshop operations are often faced with many random event perturbations,which can dis-rupt the original scheduling scheme and cause chaos and productivity loss in the workshop.In this pa-per,a hybrid rescheduling driver is used to respond to the random events by taking four scenarios as random machine failures that can be recovered,cannot be recovered or take a long time to recover,e-mergency workpiece insertion,and machine failures that occur during emergency workpiece insertion.Meanwhile,a dynamic flexible job shop scheduling model is constructed,and the crow search algo-rithm,which is originally used to deal with the continuity problem,is improved by adopting machine-based and process-based discrete coding,and designing the generation method of the three subgenera-tions to enhance the global searching capability,and avoiding the generation of local optimums with a certain probability of mutation.The IG iterative greedy algorithm is also used to increase the pionee-ring ability of the algorithm.The completion time deviation and sequence deviation are used as evalu-ation criteria to compare and analyze the right-shift rescheduling and complete rescheduling in several test cases,and at the same time,the algorithm proposed in this paper is compared with the genetic al-gorithm GA and differential evolution algorithm DE,and the experiments prove that the algorithm pro-posed in this paper has the superiority and high efficiency when testing different scheduling methods.
万方数据
维普
