Genetic algorithm using improved coding method to solve distributed flexible job shop scheduling problem

Abstract

The invention provides a genetic algorithm using an improved coding method to solve a distributed flexible job shop scheduling problem. The algorithm is suitable for the field of flexible job shop scheduling. The distributed flexible job shop scheduling problem refers to production activities carried out in several factories and manufacturing units, contains the information of flexible job shop scheduling problems, and contains the selection of suitable factories and flexible manufacturing units. The allocation of specific workpieces to different factories produces different production scheduling, which affects a supply chain. The existing technology has little research on the problem. The invention proposes the genetic algorithm to solve the problem. A traditional genetic algorithm is easy to fall into local optimum and leads to premature convergence, and the coding method produces infeasible solution and other problems. According to the invention, the improved coding method based on probability is provided; the crossover of a tabu table is introduced; the problems are avoided based on the variation of neighborhood search; and the genetic algorithm takes into account the actual production situation, and has the characteristics of high practicability and the like.

Description

[0001] Technical field [0002] The invention relates to the field of job shop scheduling, in particular to the field of distributed flexible job shop scheduling. Background technique [0003] The emergence of globalized business models and advances in technology have led to dramatic changes in the manufacturing environment. In order to be close to the market and manufacturing resources, the enterprise has evolved from a single factory to a multi-factory manufacturing environment, which has caused the scheduling system to change from a job shop scheduling system to a flexible job shop scheduling system, and even to a distributed flexible Job shop scheduling system. The distributed flexible job shop scheduling problem refers to the situation where production activities are carried out in several factories and manufacturing units. For the classic flexible job shop scheduling problem, the following problems are included: 1) the process sequence of each equipment; 2) the process...

AI Technical Summary

Problems solved by technology

[0005] The goals of this algorithm are: first, to solve the distributed flexible job shop scheduling problem, and assign the workpiece to a suitable manufacturing unit or workshop; second, to solve the problem that the coding method of the traditional genetic algorithm will generate an infeasible solution; third, to solve The genetic algorithm is easy to fall into local optimum, and the problem of premature convergence occurs

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