A Stochastic Dynamic Programming Approach to Revenue Management in a Make-to-Stock Production System

In this paper, we consider a make-to-stock production system with known exogenous replenishments and multiple customer classes. The objective is to maximize profit over the planning horizon by deciding whether to accept or reject a given order, in anticipation of more profitable future orders. What distinguishes this setup from classical airline revenue management problems is the explicit consideration of past and future replenishments and the integration of inventory holding and backlogging costs. If stock is on-hand, orders can be fulfilled immediately, backlogged or rejected. In shortage situations, orders can be either rejected or backlogged to be fulfilled from future arriving supply. The described decision problem occurs in many practical settings, notably in make-to-stock production systems, in which production planning is performed on a mid-term level, based on aggregated demand forecasts. In the short term, acceptance decisions about incoming orders are then made according to stock on-hand and scheduled production quantities. We model this problem as a stochastic dynamic program and characterize its optimal policy. It turns out that the optimal fulfillment policy has a relatively simple structure and is easy to implement. We evaluate this policy numerically and find that it systematically outperforms common current fulfillment policies, such as first-come-first-served and deterministic optimization.revenue management;advanced planning systems;make-to-stock production;order fulfillment

Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

Recent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an active role in promoting the broadening range of applications. Also technological advances, including smart shelves and radio frequency identification (RFID), are removing many of the barriers to extended revenue management. The rapid developments in Supply Chain Planning and Revenue Management software solutions, scientific models, and industry applications have created a complex picture, which appears not yet to be well understood. It is not evident which scientific models fit which industry applications and which aspects are still missing. The relation between available software solutions and applications as well as scientific models appears equally unclear. The goal of this paper is to help overcome this confusion. To this end, we structure and review three dimensions, namely applications, models, and software. Subsequently, we relate these dimensions to each other and highlight commonalities and discrepancies. This comparison also provides a basis for identifying future research needs.Manufacturing;Revenue Management;Software;Advanced Planning Systems;Demand Fulfillment

Revenue Management and Demand Fulfillment: Matching Applications, Models, and Software

Recent years have seen great successes of revenue management, notably in the airline, hotel, and car rental business. Currently, an increasing number of industries, including manufacturers and retailers, are exploring ways to adopt similar concepts. Software companies are taking an active role in promoting the broadening range of applications. Also technological advances, including smart shelves and radio frequency identification (RFID), are removing many of the barriers to extended revenue management. The rapid developments in Supply Chain Planning and Revenue Management software solutions, scientific models, and industry applications have created a complex picture, which appears not yet to be well understood. It is not evident which scientific models fit which industry applications and which aspects are still missing. The relation between available software solutions and applications as well as scientific models appears equally unclear. The goal of this paper is to help overcome this confusion. To this end, we structure and review three dimensions, namely applications, models, and software. Subsequently, we relate these dimensions to each other and highlight commonalities and discrepancies. This comparison also provides a basis for identifying future research needs

A Stochastic Dynamic Programming Approach to Revenue Management in a Make-to-Stock Production System

In this paper, we consider a make-to-stock production system with known exogenous replenishments and multiple customer classes. The objective is to maximize profit over the planning horizon by deciding whether to accept or reject a given order, in anticipation of more profitable future orders. What distinguishes this setup from classical airline revenue management problems is the explicit consideration of past and future replenishments and the integration of inventory holding and backlogging costs. If stock is on-hand, orders can be fulfilled immediately, backlogged or rejected. In shortage situations, orders can be either rejected or backlogged to be fulfilled from future arriving supply. The described decision problem occurs in many practical settings, notably in make-to-stock production systems, in which production planning is performed on a mid-term level, based on aggregated demand forecasts. In the short term, acceptance decisions about incoming orders are then made according to stock on-hand and scheduled production quantities. We model this problem as a stochastic dynamic program and characterize its optimal policy. It turns out that the optimal fulfillment policy has a relatively simple structure and is easy to implement. We evaluate this policy numerically and find that it systematically outperforms common current fulfillment policies, such as first-come-first-served and deterministic optimization

El concepto de acción en hegel

Trad. de Daniel Barreto González. México: Anthropos / Universidad autonoma metropolitana, 2010. 238 pp

Identification of Lineage-Uncommitted, Long-Lived, Label-Retaining Cells in Healthy Human Esophagus and Stomach, and in Metaplastic Esophagus

Background & Aims The existence of slowly cycling, adult stem cells has been challenged by the identification of actively cycling cells. We investigated the existence of uncommitted, slowly cycling cells by tracking 5-iodo-2'-deoxyuridine (IdU) label-retaining cells (LRCs) in normal esophagus, Barrett's esophagus (BE), esophageal dysplasia, adenocarcinoma, and healthy stomach tissues from patients. Methods Four patients (3 undergoing esophagectomy, 1 undergoing esophageal endoscopic mucosal resection for dysplasia and an esophagectomy for esophageal adenocarcinoma) received intravenous infusion of IdU (200 mg/m2 body surface area; maximum dose, 400 mg) over a 30-minute period; the IdU had a circulation half-life of 8 hours. Tissues were collected at 7, 11, 29, and 67 days after infusion, from regions of healthy esophagus, BE, dysplasia, adenocarcinoma, and healthy stomach; they were analyzed by in situ hybridization, flow cytometry, and immunohistochemical analyses. Results No LRCs were found in dysplasias or adenocarcinomas, but there were significant numbers of LRCs in the base of glands from BE tissue, in the papillae of the basal layer of the esophageal squamous epithelium, and in the neck/isthmus region of healthy stomach. These cells cycled slowly because IdU was retained for at least 67 days and co-labeling with Ki-67 was infrequent. In glands from BE tissues, most cells did not express defensin-5, Muc-2, or chromogranin A, indicating that they were not lineage committed. Some cells labeled for endocrine markers and IdU at 67 days; these cells represented a small population (<0.1%) of epithelial cells at this time point. The epithelial turnover time of the healthy esophageal mucosa was approximately 11 days (twice that of the intestine). Conclusions LRCs of human esophagus and stomach have many features of stem cells (long lived, slow cycling, uncommitted, and multipotent), and can be found in a recognized stem cell niche. Further analyses of these cells, in healthy and metaplastic epithelia, is required

Actigraphy-based sleep estimation in adolescents and adults: a comparison with polysomnography using two scoring algorithms

Objectives: Actigraphy is widely used to estimate sleep–wake time, despite limited information regarding the comparability of different devices and algorithms. We compared estimates of sleep–wake times determined by two wrist actigraphs (GT3X+ versus Actiwatch Spectrum [AWS]) to in-home polysomnography (PSG), using two algorithms (Sadeh and Cole–Kripke) for the GT3X+ recordings. Subjects and methods Participants included a sample of 35 healthy volunteers (13 school children and 22 adults, 46% male) from Boston, MA, USA. Twenty-two adults wore the GT3X+ and AWS simultaneously for at least five consecutive days and nights. In addition, actigraphy and PSG were concurrently measured in 12 of these adults and another 13 children over a single night. We used intraclass correlation coefficients (ICCs), epoch-by-epoch comparisons, paired t-tests, and Bland–Altman plots to determine the level of agreement between actigraphy and PSG, and differences between devices and algorithms. Results: Each actigraph showed comparable accuracy (0.81–0.86) for sleep–wake estimation compared to PSG. When analyzing data from the GT3X+, the Cole–Kripke algorithm was more sensitive (0.88–0.96) to detect sleep, but less specific (0.35–0.64) to detect wake than the Sadeh algorithm (sensitivity: 0.82–0.91, specificity: 0.47–0.68). Total sleep time measured using the GT3X+ with both algorithms was similar to that obtained by PSG (ICC=0.64–0.88). In contrast, agreement between the GT3X+ and PSG wake after sleep onset was poor (ICC=0.00–0.10). In adults, the GT3X+ using the Cole–Kripke algorithm provided data comparable to the AWS (mean bias=3.7±19.7 minutes for total sleep time and 8.0±14.2 minutes for wake after sleep onset). Conclusion: The two actigraphs provided comparable and accurate data compared to PSG, although both poorly identified wake episodes (i.e., had low specificity). Use of actigraphy scoring algorithm influenced the mean bias and level of agreement in sleep–wake times estimates. The GT3X+, when analyzed by the Cole–Kripke, but not the Sadeh algorithm, provided comparable data to the AWS

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

Primary pyogenic spondylitis following kyphoplasty: a case report

<p>Abstract</p> <p>Introduction</p> <p>Only ten cases of primary pyogenic spondylitis following vertebroplasty have been reported in the literature. To the best of our knowledge, we present the first reported case of primary pyogenic spondylitis and spondylodiscitis caused by kyphoplasty.</p> <p>Case presentation</p> <p>A 72-year old Caucasian man with an osteoporotic compression fracture of the first lumbar vertebra after kyphoplasty developed sensory incomplete paraplegia below the first lumbar vertebra. This was caused by myelon compression following pyogenic spondylitis with a psoas abscess. Computed tomography guided aspiration of the abscess cavity yielded group C <it>Streptococcus</it>. The psoas abscess was percutaneously drained and laminectomy and posterior instrumentation with an internal fixator from the eleventh thoracic vertebra to the fourth lumbar vertebra was performed. In a second operation, corpectomy of the first lumbar vertebra with cement removal and fusion from the twelfth thoracic vertebra to the second lumbar vertebra with a titanium cage was performed. Six weeks postoperatively, the patient was pain free with no neurologic deficits or signs of infection.</p> <p>Conclusion</p> <p>Pyogenic spondylitis is an extremely rare complication after kyphoplasty. When these patients develop recurrent back pain postoperatively, the diagnosis of pyogenic spondylitis must be considered.</p