Research On Metallurgy Equipments And Fittings Purchases Optimization Based On Fuzzy Rough Sets And Intelligence Algorithms

The optimization on the purchases of metallurgy equipments and fittings is the important topic in metallurgy enterprise purchase management. With the development of modern management methods and computer Technology, metallurgy enterprises have already realized the information technology basically, and have further developed in the macroeconomic level, it is, therefore, necessary to pay more attention on the micro level of the purchase optimization, and develop new optimization methods.This paper, based on the status of purchase management in metallurgy enterprise, puts forward a concept of fitting benefit factor firstly, which is the basic theory for purchase optimization mathematical model. And fuzzy comprehensive judgment method is applied in solving this concept. Secondly, according to the metallurgy enterprises internal purchase plan, a purchase optimization mathematical model is built, and two kinds of intelligence algorithms, called ant colony optimization algorithm and particle swarm optimization algorithm, are proposed to solve this model. Besides, the efficiency of ant colony optimization algorithm is improved by changing the cambling choosing method instead for traditional choosing method and adjusting the parameters. And the efficiency of particle swarm optimization algorithm are also enhanced by adding the random choosing and adjusting the parameters. The effectiveness of the algorithms developed above is tested by purchase optimization mathematical model. Encouraging results are obtained. Thirdly, the paper researches the problem of vendor selection in the course of purchase optimization in metallurgy enterprise. Based on the analyzing the vendor evaluation criteria and vendor selection methods ,a new methods, called rough comprehensive judgment method, is proposed to get the final partner considering in quantitative factors. The objectivity and scientific of the method raised abave are tested by an example. Finally, a purchase optimization system is designed and the basic functions of the system are analyzed detail, and the intelligence algorithms function is realized by the VC programming language and ACCESS data building language.