Integrated optimization method of equipment preventive maintenance and flexible job shop control

Abstract

The invention discloses an equipment preventive maintenance and flexible job shop scheduling integrated optimization method. The method is characterized by specifically comprising: first of all, according to an operation sequence, an equipment maintenance period, and a constraint condition of uninterrupted production process of each operation and non-conflict production process and equipment maintenance process of a flexible job shop scheduling problem, establishing an integrated optimization model of a flexible job shop scheduling and equipment maintenance plan, which takes cost and efficiency into consideration; secondary, optimizing multiple targets by use of a hybrid multi-objective chemical-reaction optimization method, the multiple targets comprising maximum completion time, total production cost and total equipment preventive maintenance cost; and finally, obtaining an optimization solving result, such that a flexible job shop scheduling plan can be obtained. The method can realize the goals of reducing the maximum completion time, the production cost and the equipment maintenance cost and can obtain an optimal flexible job shop scheduling scheme.

Description

technical field [0001] The invention belongs to the technical field of automatic production lines, and in particular relates to an optimization method of flexible workshop control technology considering equipment preventive maintenance. Background technique [0002] The Flexible Job Shop Scheduling Problem (FJSP) is a more complex so-called non-deterministic polynomial (NP-hard) problem than the traditional Job Shop Scheduling Problem (JSP). Problems, where NP refers to non-deterministic polynomial (abbreviated as NP), the so-called non-deterministic means that a certain number of operations can be used to solve problems that can be solved within polynomial time. In the flexible job shop control problem, each process of each workpiece can be processed on multiple optional processing machines, and each machine can also process different processes of multiple workpieces, and different machines can process the same The time required for the process is different, which makes th...

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Problems solved by technology

[0004] Metaheuristic methods commonly used to solve production control and equipment maintenance planning, including genetic method (GA), simulated annealing method (SA), tabu search method (TS) and particle swarm optimization method (PSO), but genetic method and particle swarm optimization method in In practical applications, disadvantages such as low local search ability and poor convergence are prone to occur. The disadvantages of simulated annealing method and tabu search method are that they do not know much about the status of the global search space and the operation efficiency is low.

[0005] Chemical-Reaction Optimization (CRO) was proposed by Lam and Li in 2010. It is a novel meta-heuristic method based on population. Compared with genetic methods and particle swarm optimization methods, it has higher optimization efficiency and robustness. However, this method also has the defects of weak local search ability and poor convergence

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