TY - JOUR

T1 - Decision-making in a single-period inventory environment with fuzzy demand

AU - Su, Rung Hung

AU - Yang, Dong Yuh

AU - Pearn, W.l.

PY - 2011/3/1

Y1 - 2011/3/1

N2 - This paper first defines the profitability to be the probability of achieving a target profit under the optimal ordering policy, and introduces a new index (achievable capacity index; IA) which can briefly analyze the profitability for newsboy-type product with normally distributed demand. Note that since the level of profitability depends on the demand mean μ and the demand standard deviation σ if the related costs, selling price, and target profit are given, the index IA is a function of μ and σ. Then, we assess level performance which examines if the profitability meets designated requirement. The results can determine whether the product is still desirable to order/manufacture. However, μ and σ are always unknown, and the demand quantity is common to be imprecise, especially for new product. To tackle these problems, a constructive approach combining the vector of fuzzy numbers is introduced to establish the membership function of the fuzzy estimator of IA. Furthermore, a three-decision testing rule and step-by-step procedure are developed to assess level performance based on fuzzy critical values and fuzzy p-values.

AB - This paper first defines the profitability to be the probability of achieving a target profit under the optimal ordering policy, and introduces a new index (achievable capacity index; IA) which can briefly analyze the profitability for newsboy-type product with normally distributed demand. Note that since the level of profitability depends on the demand mean μ and the demand standard deviation σ if the related costs, selling price, and target profit are given, the index IA is a function of μ and σ. Then, we assess level performance which examines if the profitability meets designated requirement. The results can determine whether the product is still desirable to order/manufacture. However, μ and σ are always unknown, and the demand quantity is common to be imprecise, especially for new product. To tackle these problems, a constructive approach combining the vector of fuzzy numbers is introduced to establish the membership function of the fuzzy estimator of IA. Furthermore, a three-decision testing rule and step-by-step procedure are developed to assess level performance based on fuzzy critical values and fuzzy p-values.

KW - Achievable capacity index

KW - Decision-making

KW - Fuzzy hypothesis testing

KW - Fuzzy sets

KW - Newsboy

UR - http://www.scopus.com/inward/record.url?scp=78049529492&partnerID=8YFLogxK

U2 - 10.1016/j.eswa.2010.07.123

DO - 10.1016/j.eswa.2010.07.123

M3 - Article

AN - SCOPUS:78049529492

VL - 38

SP - 1909

EP - 1916

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

IS - 3

ER -