# Download Production Engineering and Management under Fuzziness by Cengiz Kahraman, Mesut Yavuz PDF By Cengiz Kahraman, Mesut Yavuz

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Then the newsboy sells the remaining Q – D newspaper for s each, thereby losing (Q – D) (c – s). , they are crisp numbers and the probability distribution of the demand is known, optimal order quantity Q* is obtained as follows. Let FD be the cumulative distribution function of D. Then Q* that satisfies FD (Q * ) = p−c is the optimal order quantity. Using the inverse of the p−s distribution function, F-1, we summarize this result in Eq. 5). 5) ~ Kao and Hsu (2002) consider the problem with fuzzy demand D .

5. 7. Fig. 0 ) Fig. 4 ) C. Kahraman, M. Yavuz, and İ. 154) 5 Conclusions Forecasting is an important part of decision making, and many of our decisions are based on predictions of future unknown events. Forecasting is important in many aspects of our lives. We try to predict success in our occupations, and investments. Organizations invest enormous amounts based on forecasts for new products, factories, retail outlets, and contracts with executives. Decision makers need forecasts when there is uncertainty about the future.

Yavuz The addition of two fuzzy numbers: ~ x⊕~ y = ( xa + ya , xb + yb , xc + yc ) The multiplication of two fuzzy numbers: ~ x⊗~ y = ( xa ya , xb yb , xc yc ) The subtraction of two fuzzy numbers: ~ x−~ y = ( xa − yc , xb − yb , xc − ya ) The division of two fuzzy numbers: ~ x/~ y = ( xa / yc , xb / yb , xc / ya ) To defuzzify a triangular fuzzy number we define the center of gravity (cog) approach as follows. Center of gravity (cog): xcog = ∫ μ xd ∫μ d x x x x = xa + xb + xc 3 3 Economic Order Quantity The economic order quantity (EOQ) is the simplest and most fundamental of inventory models.