Dynamic flexible job-shop scheduling method based on multi-objective evolutionary algorithm

Abstract

The invention discloses a dynamic flexible job-shop scheduling method based on a multi-objective evolutionary algorithm. The dynamic flexible job-shop scheduling method based on the multi-objective evolutionary algorithm mainly aims to solve the problems that existing methods are poor in dynamic change environment adaptive ability and low in search efficiency. The dynamic flexible job-shop scheduling method based on the multi-objective evolutionary algorithm comprises the first step of carrying out initialization, specifically, reading information of jobs, machine attributes and the like, defining an optimal object and setting a constraint condition, the second step of simultaneously optimizing time of completion, tardiness and the maximum machine loading based on a static multi-objective evolutionary algorithm at initial moments, and the third step of adopting a rescheduling mode driven by emergent dynamic events in a shop production process, quickly generating a new scheduling scheme in a new environment based on a dynamic multi-objective evolutionary algorithm in order to simultaneously optimize the time of completion, tardiness, the maximum machine loading and stability of workpieces to be scheduled. Compared with a traditional scheduling method, the dynamic flexible job-shop scheduling method based on the multi-objective evolutionary algorithm can timely respond to happening of emergent dynamic events, adjust a search strategy in a self-adaptation mode according to the dynamic environment, and the generated scheduling scheme has the advantages of being high in efficiency and excellent in stability.

Description

technical field [0001] The invention relates to the field of flexible job shop scheduling control, which can be used to realize the machine allocation of each job procedure and the scheduling of processing sequences in a dynamically uncertain flexible job shop production environment. Background technique [0002] The flexible job shop scheduling problem refers to establishing a flexible job shop scheduling model, assigning appropriate machines to each process of each job through a certain algorithm, and determining the processing sequence of the processes on each machine, so as to satisfy various constraints. Under the premise, to achieve the optimization goals such as the shortest completion time of the job, the minimum delay, and the load balance of each machine. [0003] The production environment of the actual flexible job shop is dynamic and uncertain, and there are many dynamic factors such as "new job release", "machine failure", "faulty machine repair" and so on. Wh...

AI Technical Summary

Problems solved by technology

[0006] 1) Most of them only consider the static production environment, and they assume that all the information in the flexible job shop is known in advance and fixed. Obviously, when the actual production environment changes dynamically or there are uncertain factors, according to the static method The schedule for is no longer applicable

[0007] 2) Although some dynamic scheduling methods have emerged, most of them only consider the impact of dynamic events on workshop productivity (such as completion time)

[0008] 3) The processing method for multiple optimization objectives is relatively simple

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