Production line online dynamic scheduling method based on decomposition-based multi-objective optimization algorithm

Abstract

The invention provides a production line online dynamic scheduling method based on a decomposition-based multi-objective optimization algorithm, and relates to the technical field of workshop dynamicscheduling. The method mainly solves the problems that an existing method is low in adaptability to a dynamic event and has to be shut down when the dynamic event is processed, and comprises the stepsthat firstly, initialization is conducted, information of a workpiece, a machine and the like is read, an optimization target model is established, and constraint conditions are given; at the initialmoment, a decomposition-based multi-objective optimization algorithm is used to optimize the completion time, the total tardiness, the total load of the machine, the energy consumption and other objectives at the same time; and in a workshop production process, a hybrid drive rescheduling mode is adopted, and a new dynamic rescheduling optimization scheme can be quickly generated in a new environment by using a decomposition-based multi-objective optimization algorithm under the condition of non-stop continuous work, so that the completion time, the total tardiness, the total load of the machine and the energy consumption of a workshop are optimized at the same time.

Description

technical field [0001] The invention relates to the technical field of workshop dynamic scheduling, in particular to an online dynamic scheduling method of a production line based on a decomposition-based multi-objective optimization algorithm. Background technique [0002] The flexible job shop scheduling problem is an extended form of the traditional job shop scheduling problem, and it is an NP-hard problem. Workshop scheduling includes process scheduling and machine scheduling. Flexible workshop scheduling is more complicated because each process can be processed on at least one machine. Under the premise of satisfying the constraint conditions through a certain algorithm, the optimization goals such as the shortest maximum completion time of the workpiece, the minimum total delay, the minimum maximum load of the machine, and the minimum energy consumption are achieved. [0003] However, in the actual production workshop, there are many dynamic disturbances, such as "new...

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Problems solved by technology

[0006] (1) Most of them only consider the situation where workpieces and machines are determined, and do not consider the interference of dynamic events, which is inconsistent with the actual production workshop and is not suitable for the actual workshop

[0007] (2) Most of the existing dynamic scheduling methods only consider the optimization of the maximum completion time and only use a single rescheduling method, without considering other factors that will affect the overall optimization effect of the workshop, and without considering energy consumption and workpieces Transfer between machines, etc.

[0008] (3) The existing multi-objective optimization method is relatively single

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