Balance improvement method used for collaborative robot assembling line and based on genetic algorithm

Abstract

The invention discloses a balance improvement method used for a collaborative robot assembling line and based on a genetic algorithm. By virtue of the method, balance ratio of the collaborative robotassembling line can be the highest. The method comprises the following specific steps: (1) inputting related information of the collaborative robot assembling line; (2) analyzing a preferential constraint relation among all the working procedures on the collaborative robot assembling line, and drawing a working procedure constraint graph; (3) according to the working procedure constraint graph, generating initial population, and performing a gene crossover operation and a mutation operation on the initial population; (4) partitioning stations by utilizing a maximum allocation principle, calculating a balance ratio of each station, and eliminating an individual with low balance ratio; and (5) judging whether gene sequences of the population are completely the same or not, if the gene sequences of the population are not completely the same, repeating the steps (3) and (4) until the gene sequences of the population are completely the same, and then outputting the gene sequences of the population as well as a station partitioning method of the population.

Description

technical field [0001] The invention relates to the technical field of production line balance improvement, in particular to a method for improving the balance of a collaborative robot assembly production line based on a genetic algorithm. Background technique [0002] Production line balance refers to adjusting the position of each process in the production line so that the time of each station is as equal or similar to the production beat as possible. [0003] At present, the balance optimization of the production line is mainly aimed at the following two situations. The first is that the production line sets a specific production beat under a given workload, and then optimizes the assembly sequence of the production line so that the The difference in working hours is the smallest; the second is to determine the number of stations in the production line, and reduce the production tact of the production line as much as possible, so as to maximize the output of the productio...

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Problems solved by technology

[0004] Fang Jingfang and Xu Yankai proposed a production line balance optimization method based on genetic algorithm in the literature "Based on Traversal Search and Genetic Algorithm for Production Line Balance Optimization", but this method did not judge the quality of offspring genes and did not simulate The process of survival of the fittest in nature, although this method can also obtain the optimal solution through a large number of genetic algorithm operations, but because the pros and cons of offspring genes are random, it will undoubtedly take a lot of time

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