The Multi-Order Conversion Costs Based On Hybrid Particle Swarm Optimization Algorithm

Order conversion is very frequent in an order enterprise, when an order converses to another, it means increasing so much cost.In the study of order conversion cost, the researchers mainly focuse on the fields of economics, especially the marketing aspects, while in the field of manufacturing industry,the researchers is so few, this paper will preliminarily study the multi-order conversion cost of the manufacturing industry.Analyse the cost characteristics and limitations of the order enterprises,obtain the four key factors which influences order conversion cost by means of expert group method:tools depreciation cost,human resources cost, material (energy) cost and time delay costs in conversion.And establish the order conversion cost model based on these factors,eventually establishe the simplified multiple order conversion cost model. Intelligent optimization algorithms are often used to solve the nonlinear optimization problem.This paper discusses the ideas and computation processes of the genetic algorithm and particle swarm algorithm and discusses the improved particle swarm algorithm and improved genetic algorithm,then Put forward a kind of hybrid particle swarm optimization algorithm which can effectively avoid the slow convergence and premature convergence.Finally, this research is applied to the practice. Take a well-known automotive interior company as an example, make a detailed calculation for the conversion cost of the four key factors.Apply hybrid particle swarm algorithm to achieve a minimum conversion coss about the company’s10products’conversion and provide reference for the company’s decision-making.