Flexible workshop scheduling method for solving belt transportation time based on improved cultural gene algorithm

Abstract

The invention relates to an improved cultural gene algorithm for solving a flexible job shop scheduling method with transportation time, which can effectively solve a flexible job shop scheduling scheme with transportation time. According to the technical scheme, the method comprises the following steps; 1, setting parameters; 2, generating an initial population through three initialization methods; 3, calculating a current optimal solution; 4, judging whether the algorithm is terminated or not; 5, executing a mutation operator; 6, forming a new population; 7, calculating the maximum completion time of the population individuals. The encoding mode is simple and easy to implement, the algorithm operation efficiency is improved, repeated search of neighborhood solutions of excellent individuals is avoided through the elite library and the mutation probability, and the search efficiency is improved.

Description

technical field [0001] The invention relates to the field of flexible job shop scheduling, in particular to a method for solving flexible job shop scheduling with transportation time by an improved cultural gene algorithm. Background technique [0002] In recent years, more and more efficient intelligent automated production methods have attracted widespread attention from the society. Products are developing in a more personalized and customized direction, and the assembly line production organization is more flexible, which makes the scheduling problem more complicated. Flexible Job Shop Scheduling Problem (FJSP) is an NP-hard combinatorial optimization problem, and it is an important extension of Job Shop Scheduling Problem (JSP). In the JSP problem, the process of the workpiece corresponds to the machine one by one, which is not in line with the actual production status. In the FJSP problem, the processing machine for each process is not unique, and the processing time ...

AI Technical Summary

Problems solved by technology

[0003] At present, there are group search algorithms and local search algorithms based on meta-heuristics to solve the FJSP problem. However, these algorithms have defects and deficiencies to a certain extent. The group search algorithm has low search accuracy and slow convergence speed; the local search algorithm has a small search range. , easy to fall into the local optimal solution

Secondly, the FJSP problem with transportation time is more in line with the actual requirements, but there are few efficient and fast algorithms proposed

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