Hybrid optimization method for flexible assembly job shop scheduling

Abstract

The invention provides a hybrid optimization method for flexible assembly workshop scheduling. The hybrid optimization method comprises the following steps: S1, determining known information and algorithm parameters of flexible assembly workshop scheduling; s2, adding a label to the workpiece for subsequent use; s3, generating an initial population of feasible solutions by utilizing the known information of the problem, and encoding the schedule of each feasible solution in the population in the form of a task sequence; s4, selecting some individuals from the population through competition, performing crossover and mutation gene operation on the individuals, and performing search in neighborhoods of the known feasible solutions by changing a processing plan and machine selection to obtainnew feasible solutions; s5, for each feasible solution in the population, optimizing the processing sequence by using a constraint programming model to form a new solution and update the population; and S6, repeating the steps S4 and S5, and performing iteration until a termination condition, namely the total running time or the total number of iterations, reaches a preset limit.

Description

technical field [0001] The invention belongs to the field of production operation management, and relates to a method for solving the scheduling problem of a dynamic flexible assembly workshop, emphasizing the flexible and non-linear processing process of each assembly part, the batch splitting problem of multiple identical parts, and the gap between different assembly products. parts sharing. Background technique [0002] With the rapid development of the economy, my country has established a complete and independent manufacturing system, which has promoted the process of industrialization. Among them, intelligent manufacturing projects have attracted extensive attention from academia and industry. Scheduling problem is a kind of important problem in intelligent manufacturing system, and it is also a hotspot of academic research. It mainly focuses on the utilization of manufacturing resources such as personnel, materials, and machines. Meet the constraints of processing te...

AI Technical Summary

Problems solved by technology

Secondly, job shop scheduling seldom considers the final assembly stage; relatively speaking, in assembly line scheduling, assembly considerations are more common. There is a gap in the actual customized production process

Furthermore, most of the previous studies were based on static environments, and less consideration was given to various uncertain factors in the actual execution of production plans, such as machine failures, pipeline blockages, processing time fluctuations, etc. Scheduling performance is significantly reduced, and even becomes unfeasible; and the dynamic assembly environment requires that each assembly part should be flexibly taken during the actual production process, rather than pre-assigned to a specific product, in order to eliminate the adverse effects of uncertainty

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