Multi-objective optimized overall workshop layout method based on multi-population genetic algorithm

Abstract

The invention discloses a multi-objective optimized overall workshop layout method based on a multi-population genetic algorithm. The method comprises the following steps: firstly, a multi-row linearworkshop layout mathematical model is established, and a functional area layout problem is converted into a combined optimization mathematical model problem; secondly, based on the optimization objective of minimum total material handling cost and maximum area utilization ratio of workshop layout, a precise workshop layout model is established by taking account of constraints including horizontaland vertical placement of main streets and functional areas, adaptive row spacing and the like of the manufacturing workshop, and multiple optimization objectives are converted into a single evaluation function with a weighting method; finally, solving is performed with the multi-population genetic algorithm, immigration operators are linked with populations in the solving process, information exchange and co-evolution of multi-population are achieved, different crossover and mutation probability parameters are set for different populations by crossover and mutation probability control formulae, and different search purposes are guaranteed. The total logistics handling cost of the workshop can be effectively reduced, and the utilization rate of the workshop area is increased.

Description

technical field [0001] The present invention relates to the technical field of multi-objective optimization of workshop layout, in particular to a multi-objective optimization overall layout method for workshops based on multi-population genetic algorithm, which not only includes accurate modeling of workshop layout, but also includes multi-population genetic algorithm to solve the mathematical model specific process. Background technique [0002] With the increasingly fierce market competition, enterprises are required to accurately or restructure the layout of production workshops to adapt to the rapid changes in the market. As described in the literature [Braglia M, Zanoni S, Zavanella L. Layout design indynamic environments: Strategies and quantitative indices [J]. International Journal of Production Research, 2003, 41(5): 995-1016.], the materials of an enterprise workshop The handling cost is about 20% to 50% of the total manufacturing cost, and optimizing the worksho...

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Problems solved by technology

[0004] Although scholars have done a lot of research on the workshop problem, the mathematical model of the workshop layout established is too simplified, which often leads to a large difference between the mathematical model and the actual physical model, such as the horizontal and vertical layout of the unequal functional area. Placement problems, as well as on-site practical problems such as vertical main roads and variable line spacing, and the goal of optimization is usually a single goal of minimizing material handling costs, while ignoring the influence of factors such as the area utilization rate of the workshop, which is not very practical. The choice of crossover and mutation probability parameters in the standard genetic algorithm used in the solution has a great influence on the results, but under the full consideration of the actual constraints on the site, a more accurate mathematical model of the overall layout of the workshop can be established, and it is more effective to use the solution The multi-population genetic algorithm realizes the multi-objective solution of the precise layout model and improves the solution accuracy

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