外文翻譯---供應(yīng)鏈管理環(huán)境下的庫(kù)存優(yōu)化-環(huán)境工程(編輯修改稿)
2025-06-26 10:42 本頁(yè)面
【文章內(nèi)容簡(jiǎn)介】 factors which affect the inventory is nonlinear, so it is difficult to make a quantitative and definite mathematical relationship, also the optimum results cannot meet the applications in the realworld. Artificial neural work have the ability to learn by itself and multimapping, and it can explore plicate system escaping to make plicate models. In the artificial neural work models, the information hides in the work made by linkedneuron, and it can deal with multiple quantitative relationships. Namely, the ANN is a massively parallel putational model, and it has characterizes : Great degree of robustness and fault tolerance。 Ready to deal with problems associated with general nonlinear systems。 Biophysical implications. So ANN is a good analysis tool for nonlinear problem. This paper will put forward to improve traditional inventory models with the aid of multi layer BP neural work so as to acquire much more satisfactory optimum tactics of inventory. LIMITATION TRADITIONAL INVENTORY OPTIMUM MODEL Before the strategic alliance relationship among the upstream and downstream enterprises es into being, there is only a single material flow. The operational mechanics is shown below: Under the operational mechanies of traditional supply chain(as show in figurel)， making inventory optimurn models。 because of the lack of the necessary information, have to utilize probabilistic models to fit the changes of requirements based on the information of statistics. Now we give a simple single period random inventory model: In this model: E[T (y)] :The value of expectation of the total cost of inventory。 c :The manufacture(or purchase)cost of per product。 h: The inventory cost of per product。 p :The punishment cost for shorts of per product。 x: The opening stock。 y :The stock obtained at opening。 ξ: The demand during this epoch, it is a random variable。 φ(ξ):The probability density function of ξ. In order to minimize the value of E[T(y)],namely， this must have .Following the method of derivation formulation which obtains parameter argument, we will get 。If give the value of c , h , p ,we can get the optimum value of stock y39。 。also we can get the optimum inventory tactics during this epoch. As referred above, this traditional model is made under the insufficient information, so it is essential to lead many premise hypotheses, delimitate the application range, so this kind of model is difficult to accord with the application in the realworld. The main problem focus on the probability density functions of ξ .From the analysis above we know the factors which affect the random variable ξ are a multivariable nonlinear relationship。 such as: the price of product, the change of marketing seasons, the internal rate of return of total vocation. Of cause, as for a specific enterprise ,the factors may be variable ξ may not conform to a
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