Genetic algorithm workshop production scheduling method based on virtual process

Abstract

The invention provides a genetic algorithm workshop production scheduling method based on a virtual process, and the method comprises the following steps: reading a production scheduling task, extracting production scheduling data in a production scheduling order, and carrying out the standardization processing of the production scheduling data; converting the standardized production scheduling data into virtual process production scheduling data according to a virtual process representation rule; processing the virtual process scheduling data by using a genetic algorithm added with an immigrant strategy and an optimal storage strategy, and decoding an optimal individual output by the genetic algorithm to obtain an optimal workshop scheduling result; and visually displaying the output optimal workshop production scheduling result on a user interface. According to the virtual procedure processing, the solving difficulty of the genetic algorithm in solving the complex production scheduling problem is greatly simplified, and the algorithm solving speed is increased. The scheduling problem is modeled and solved by using the genetic algorithm, the order delivery delay is reduced, the product turnover rate is improved, and the defect of manual scheduling is overcome; and the global convergence of the algorithm is ensured through the optimal storage strategy and the immigrant strategy.

Description

technical field [0001] The present invention relates to the technical field of intelligent workshop scheduling and scheduling, in particular to a genetic algorithm workshop scheduling method based on a virtual process, which constructs multi-objective constraint conditions and solves them through a genetic optimization algorithm to optimize workshop scheduling. Background technique [0002] In the field of intelligent workshop scheduling, the current mainstream technical solution is to use heuristic algorithms, such as genetic algorithm, particle swarm algorithm, simulated annealing algorithm, etc., and various methods for improving these heuristic algorithms. Taking the mainstream genetic algorithm as an example in workshop scheduling, it is generally divided into the following steps: [0003] 1. Coding, the data represented by a set of specific rules represent possible solutions to the production scheduling problem. [0004] 2. Decoding, convert the obtained solution into...

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Problems solved by technology

[0014] In view of the existing heuristic algorithms, such as genetic algorithms, in the face of complex processing scenarios, there are technical problems such as difficult to design chromosome coding methods and long solution time, the present invention proposes a genetic algorithm workshop scheduling method based on virtual processes, using The virtual process simplifies the original problem, and then uses the genetic algorithm to solve the simplified production scheduling problem. The coding design and solution difficulty speed of the production scheduling problem are greatly reduced compared with the original problem; The premature phenomenon that may appear in the later stage; through the optimal preservation strategy, the survival life of excellent individuals is extended, and the global convergence of the genetic algorithm is guaranteed

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