Genetic scheduling method based on combined production and equipment fault constraint

Abstract

The invention discloses a genetic scheduling method based on combined production and equipment fault constraints, is used for a workshop flexible job scheduling technology, and relates to the technical field of automatic control. The problem of production scheduling of a processing production line is solved by constructing an operation constraint graph model, and meanwhile, operation is completed on a healthy machine to the greatest extent by introducing a machine failure rate-based wheel disc selection method, so that the scheduling delay during equipment failure is reduced, the fitness calculation of a production line genetic scheduling algorithm is optimized and combined. An experiment result shows that compared with a scheduling method based on a genetic algorithm, the intelligent scheduling algorithm has the advantages that better initialized population, convergence and robustness can be obtained, the problem of intelligent scheduling of the combined production line is solved, and meanwhile, the possibility of machine loss faults is considered; and thus, flexible job shop scheduling is realized.

Description

technical field [0001] A genetic scheduling method based on combined production and equipment failure constraints is used in workshop flexible job scheduling technology, and the invention relates to the technical field of automatic control. Background technique [0002] Aiming at the planning and scheduling problems in the operation of various processing production lines under the intelligent manufacturing mode, major research institutions and the industrial world are focusing on research on production planning scheduling and intelligent scheduling technology methods. The existing research methods are mainly based on the application of heuristic algorithms. Including meta-heuristic scheduling algorithm, scheduling algorithm based on genetic algorithm, scheduling algorithm based on particle swarm optimization, scheduling algorithm based on deep reinforcement learning, and multi-objective scheduling algorithm; among them, the two-stage algorithm based on imperial competition al...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a genetic scheduling method based on combined production and equipment failure constraints, to explore an efficient method for the problem that the combined production process depends on the products of multiple previous processes and the existence of machine failures in the complex combined production line scheduling process. High, stable and practical flexible job shop scheduling method

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