Clipping bed separation method based on speedup-factor adaptive particle swarm optimization

Abstract

The invention discloses a clipping bed separation method based on speedup-factor adaptive particle swarm optimization. The method comprises the following steps that: S1: setting an initial limiting condition and the parameter of the SAPSO (Speedup-factor Adaptive Particle Swarm Optimization) for clipping bed separation; S2: according to the initial limiting condition set by a user, calculating a possible bed separation amount: calculating the sum of the amounts of sample sheets which need to be clipped, average each-bed cloth laying layer number and average each-layer cloth clipping piece number according to the amount of sample sheets, which need to be clipped, of each model so as to calculate the upper limit and the lower limit of a required bed separation amount; and S3: firstly, searching a bed separation scheme with a small bed number, if the scheme with the small bed number conforms to requirements, stopping searching a situation with a large bed number, and if the bed separation scheme with the small bed number does not conform to the requirements, searching a bed separation scheme with the large bed number. Under a situation of a certain bed separation bed number, the SAPSO is adopted to search the cloth laying layer number. By use of the method, bed separation scheme determining efficiency is improved, material budgets are reduced, and a clipping amount error is reduced.

Description

technical field [0001] The invention belongs to the technical field of industrial numerical control equipment automation, and relates to a method for cutting and dividing beds on a cutting bed. Background technique [0002] China is a country with a large population and the largest garment producer and consumer in the world. In recent years, with the fluctuation of the RMB exchange rate, the cost of hiring workers and producing raw materials for enterprises has become higher and higher, making it more and more difficult for enterprises to survive. Especially in recent years, prices have risen rapidly, resulting in a large labor gap and difficulty in recruiting workers. The clothing industry is a traditional labor-intensive enterprise, and it is even more difficult to survive and develop. Therefore, if an enterprise wants to stand firm in the environment of fierce market competition and rising production cost, it must start from the perspective of reducing production cost a...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the shortcomings of long time-consuming, large error and low efficiency in determining the current method of cutting and dividing beds, the present invention introduces a modern intelligent optimization algorithm and provides a cutting and dividing method based on the SAPSO algorithm, which improves the efficiency of determining the bed dividing scheme and reduces The material budget is improved, and the cutting quantity error is reduced

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