Research On One-shot Decision Making Of Single-period Product Based On Probability Distribution

The single period products usually have the characteristics of short-shelf life,strong timeliness,fast circulation speed and large demand fluctuation.Generally,this kind of product is purchased according to the demand cycle,if it is assumed that the demand of the product can be predicted,the order quantity is the key to control the single-period inventory,through the best order quantity in order to achieve the largest sales revenue.Therefore,the choice of a one-shot decision theory to solve this problem in daily life will usually meet the needs of the fuzzy single-period product ordering problem has immensely important practical significance.Based on the research of one-shot decision theory,this paper studies the single-period product ordering problem based on probability distribution.In this paper,I assume that the information of the natural state distribution is completely known,and that it is with a certain type of probability distribution.Based on the one-shot decision theory under the possibility distribution,further concluded that the one-shot decision procedure based on probability distribution.Twelve types of focus points in the case of probability distribution are derived,and compare the satisfaction level of each type of focus points provided by different orders,resulting in twelve kinds of optimal order quantities.In this paper,the problem of yogurt as a numerical example,an analysis is conducted to illustrate the process of such a one-shot decision,and how to use one-shot decision to obtain the best order quantity.It turned out that the proposed one-shot decision can help decision makers to determine their reasonable order quantity in the case of the demand probability distribution known,to maximize the sales revenue through the optimization of the order quantity.We can obtain a one-shot decision method which can be applied to the majority of sales and time related commodity ordering problem in the case of probability distribution known.For example,some holiday commodity ordering(mid autumn moon cakes and Valentine’s Day roses reservation,etc.),fresh goods ordering,fashion magazines ordering and so on.