In 4c the robability of loss is bounded from above by the secified value PL. The so-called critical ratio reresents the rofit value of the roduct and describes the cycle service level in-stock robability related to the otimal exected rofit.
Here condition 17 is violated. The admissible region for the order quantity and the selling rice are characterized both for the multilicative and the additive demand model.
We illustrate the structural roerties by means of some examles.
The urchase rice er unit of the roduct is c. Figure 3 illustrates the statement of Proosition 3. The like the to-level erformance measures of the suly chain oerations reference SCOR model are categorised into internal costs, assets and external reliability, resonsiveness, flexibility measures see www.
This is an easy consequence from 7. Stoyan Comarison methods for stochastic models and risks. Omega 37, Yao, L. Let F and G be two distribution functions and assume that 7 is fulfilled for F.
The random demand X is characterized by the distribution function F. By CSL we denote a given lower bound for the cycle service level. The newsvendor model is one of the fundamental oerations models that is rich enough to gain imortant managerial insights see Porteus Figure 1 illustrates condition 8.
For the additive and the multilicative demand models Chen et al. We denote by X the random demand for rice with distribution function F. Characterisation of the otimal solution for uniformly distributed demand over [0,b] 3 Price-Setting Newsvendor with Service and Loss Constraints 3.
In Gan et al. Let y denote the order quantity and g the rofit. For given demand distribution F and for given PL and CSL condition 7 can be used to describe the range of admissible rice arameters, c and z.
The classical newsvendor model with service and loss constraints is resented and analysed in section 2. It turns out that the otimal quantity solves the tradeoff resulting from the costs from ordering too many and the costs from ordering too few units of the roduct.
Furthermore, it is shown that higher variability of demand leads to a smaller admissible region of the decision variables thereby easing the comutation of the otimal decisions.
Moreover it is shown that higher variability of demand leads to a smaller admissible region of the decision variables thereby easing the comutation of the otimal order quantity and the otimal selling rice. This means, the lower the demand variability the more likely an otimal order quantity exists.
Weib 3dashed lines: Illustration of condition 8 for distribution functions F and G 2. But these findings may not be desirable for high-rofit and low-rofit roducts in general as is indicated by exerimental and emirical studies see e.
Admissible regions for the additive model with uniform distribution Dotted lines: Note that its otimal solution is given by 3. Therefore, for high-rofit roducts the existence of a solution is more likely than for low-rofit roducts.
Like in the model with rice indeendent demand we investigate the influence of demand uncertainty on the region of admissible rices and order quantities.
Like in the multilicative model the qualitative roerties resented in Proosition 3 hold. The condition for the existence of an otimal order quantity can be used to secify rice arameters of the model. Fransoo Entrereneurs and newsvendors: Unif 0,2 It has to be noticed that the otimal order quantity cannot exceed the maximal demand for a given selling rice.Jena Research Paers in Business and Economics A newsvendor model with service and loss constraints Werner Jammernegg und Peter Kischka 21/ Jenaer Schriften zur Wirtschaftswissenschaft Working and Discussion.
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