Implementation of the Newsvendor Model with Clearance Pricing: How to (and How Not to) Estimate a Salvage Value

The newsvendor model is designed to decide how much of a product to order when the product is to be sold over a short selling season with stochastic demand and there are no additional opportunities to replenish inventory. There are many practical situations that reasonably conform to those assumptions, but the traditional newsvendor model also assumes a fixed salvage value: all inventory left over at the end of the season is sold off at a fixed per-unit price. The fixed salvage value assumption is questionable when a clearance price is rationally chosen in response to the events observed during the selling season: a deep discount should be taken if there is plenty of inventory remaining at the end of the season, whereas a shallow discount is appropriate for a product with higher than expected demand. This paper solves for the optimal order quantity in the newsvendor model, assuming rational clearance pricing. We then study the performance of the traditional newsvendor model. The key to effective implementation of the traditional newsvendor model is choosing an appropriate fixed salvage value. (We show that an optimal order quantity cannot be generally achieved by merely enhancing the traditional newsvendor model to include a nonlinear salvage value function.) We demonstrate that several intuitive methods for estimating the salvage value can lead to an excessively large order quantity and a substantial profit loss. Even though the traditional model can result in poor performance, the model seems as if it is working correctly: the order quantity chosen is optimal given the salvage value inputted to the model, and the observed salvage value given the chosen order quantity equals the inputted one. We discuss how to estimate a salvage value that leads the traditional newsvendor model to the optimal or near-optimal order quantity. Our results highlight the importance of understanding how a model can interact with its own inputs: when inputs to a model are influenced by the decisions of the model, care is needed to appreciate how that interaction influences the decisions recommended by the model and how the model’s inputs should be estimated

Co-firing of biomass with coals Part 1. Thermogravimetric kinetic analysis of combustion of fir (abies bornmulleriana) wood

The chemical composition and reactivity of fir (Abies bornmulleriana) wood under non-isothermal thermogravimetric (TG) conditions were studied. Oxidation of the wood sample at temperatures near 600 A degrees C caused the loss of aliphatics from the structure of the wood and created a char heavily containing C-O functionalities and of highly aromatic character. On-line FTIR recordings of the combustion of wood indicated the oxidation of carbonaceous and hydrogen content of the wood and release of some hydrocarbons due to pyrolysis reactions that occurred during combustion of the wood. TG analysis was used to study combustion of fir wood. Non-isothermal TG data were used to evaluate the kinetics of the combustion of this carbonaceous material. The article reports application of Ozawa-Flynn-Wall model to deal with non-isothermal TG data for the evaluation of the activation energy corresponding to the combustion of the fir wood. The average activation energy related to fir wood combustion was 128.9 kJ/mol, and the average reaction order for the combustion of wood was calculated as 0.30

The Top-Dog Index: A New Measurement for the Demand Consistency of the Size Distribution in Pre-Pack Orders for a Fashion Discounter with Many Small Branches

We propose the new Top-Dog-Index, a measure for the branch-dependent historic deviation of the supply data of apparel sizes from the sales data of a fashion discounter. A common approach is to estimate demand for sizes directly from the sales data. This approach may yield information for the demand for sizes if aggregated over all branches and products. However, as we will show in a real-world business case, this direct approach is in general not capable to provide information about each branch's individual demand for sizes: the supply per branch is so small that either the number of sales is statistically too small for a good estimate (early measurement) or there will be too much unsatisfied demand neglected in the sales data (late measurement). Moreover, in our real-world data we could not verify any of the demand distribution assumptions suggested in the literature. Our approach cannot estimate the demand for sizes directly. It can, however, individually measure for each branch the scarcest and the amplest sizes, aggregated over all products. This measurement can iteratively be used to adapt the size distributions in the pre-pack orders for the future. A real-world blind study shows the potential of this distribution free heuristic optimization approach: The gross yield measured in percent of gross value was almost one percentage point higher in the test-group branches than in the control-group branches.Comment: 22 pages, 15 figure

Application of recent advances in hydrodynamic methods for characterising mucins in solution

Mucins are the primary macromolecular component of mucus—nature’s natural lubricant—although they are poorly characterised heterogeneous substances. Recent advances in hydrodynamic methodology now offer the opportunity for gaining a better understanding of their solution properties. In this study a combination of such methods was used to provide increased understanding of a preparation of porcine intestinal mucin (PIM), MUC2 mucin, in terms of both heterogeneity and quantification of conformational flexibility. The new sedimentation equilibrium algorithm SEDFIT-MSTAR is applied to yield a weight average (over the whole distribution) molar mass of 7.1 × 106 g mol−1, in complete agreement with size exclusion chromatography coupled with multi-angle light scattering (SEC-MALS), which yielded a value of 7.2 × 106 g mol−1. Sedimentation velocity profiles show mucin to be very polydisperse, with a broad molar mass distribution obtained using the Extended Fujita algorithm, consistent with the elution profiles from SEC-MALS. On-line differential pressure viscometry coupled to the SEC-MALS was used to obtain the intrinsic viscosity [η] as a function of molar mass. These data combined with sedimentation coefficient data into the global conformation algorithm HYDFIT show that PIM has a flexible linear structure, with persistence length Lp ~10 nm and mass per unit length, ML ~2380 g mol−1 nm−1, consistent with a Wales-van Holde ratio of ~1.2 obtained from the concentration dependence of the sedimentation coefficient

Kinetic analysis of Central Anatolia oil shale by combustion cell experiments

In this study, four oil-shale samples (Nigde-Ulukisla) excavated from Central Anatolia Turkey were analyzed where this region is believed to have a high potential of oil in its shale rich outcrops. The samples (similar to 40 g) were combusted at 50 psi gas injection pressure, at an air injection rate of 1.5 L min(-1) in a combustion-reaction cell. All the experiments were conducted up to 600 degrees C. The percentages of oxygen consumption and carbon monoxide and carbon dioxide production were obtained instantaneously with respect to time. The combustion periods and relative reaction rates were determined by examining the effluent gas concentration peaks. Activation energies of the samples were determined using Weijdema's approach. It was observed that the activation energies of the samples are varied between 22-103 kJ mol(-1)

Effects of polymers and CMC concentration on rheological and fluid loss parameters of water-based drilling fluids

Fluid loss during drilling operations has a very significant effect on both reservoir formation damage and monetary terms. There are many additives to control this unwanted phenomenon. Nevertheless, most of these substances are artificial chemicals. Thus, they are not only expensive, but also hazardous to the environment. In this article, a more natural method was applied to overcome the higher filtration problems by employing carboxyl methyl cellulose (CMC) and polymers (XT), DSHV, and MAC PR. Drilling fluids were prepared due to American Petroleum Institute (API) standards. The fluid weights were adjusted as 9 ppg. API filtration tests were applied to fluid samples including the chemicals. Tests were also conducted with non-treated bentonites + barite fluids without chemicals for comparative purposes. All of the rheological parameters including plastic and apparent viscosity and yield points were determined. Comparative graphs of shear stress vs. shear rates were plotted. The optimum CMC and polymer amounts were selected by graphical analysis of the results of rheological tests made by using shear meter and filtration tests. An optimization of the fluid loss control due to addition of the chemicals was made. The behavior of water-based fluids with CMC and polymers was examined. The accurate and sensitive industrial application of this study would reduce drilling fluid loss expenditures effectively

Estimation of Filter Cake Thickness for Water-based Drilling Fluids

It is obvious that estimation of filter cake thickness is one of the important parameters in drilling operations. In this study, dynamic filtration data was used to determine the filter cake thickness. Predictions were made through linear filtration cake model by using dynamic filtration experimental data. Linear filtration model can be used to approximate radial filtration model; only the thickness of the filter and filter cake is sufficiently smaller than the radius of the filter surface exposed to slurry. It was observed that the thickness of the filter cake at dynamic conditions is less than that of static conditions since there is no continuous deposition due to erosion effects at dynamic conditions