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We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast-shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast-ship option. We find a range of markups for fast-ship orders such that the fast-ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win-win for both players may not exist even when offering fast-ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast-ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast-ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast-ship option because the supplier may choose not to support the fast-ship option when fast-ship participation increases due to the fact that the fast-ship participation rate adversely affects the initial order size. [ABSTRACT FROM AUTHOR]

Transit agencies use reserve drivers to cover open work that arises from planned and unplanned time off, equipment breakdowns, weather, and special events. Work assignment decisions must be made sequentially without information about future job requests, a driver’s earlier assignment may not be interrupted to accommodate a new job (no pre-emption), and the scheduler may need to select a particular driver when multiple drivers can perform a job. Motivated by this instance of the interval scheduling problem, we propose a randomized algorithm that carries a performance guarantee relative to the best offline solution and simultaneously performs better than any deterministic algorithm. A key objective of this article is to develop an algorithm that performs well in both average and worst-case scenarios. For this reason, our approach includes discretionary parameters that allow the user to achieve a balance between a myopic approach (accept all jobs that can be scheduled) and a strategic approach (consider accepting only if jobs are longer than a certain threshold). We test our algorithm on data from a large transit agency and show that it performs well relative to the commonly used myopic approach. Although this article is motivated by a transit industry application, the approach we develop is applicable in a whole host of applications involving on-demand-processing of jobs. Supplementary materials are available for this article. Go to the publisher’s online edition ofIIE Transactionsfor datasets, additional tables, detailed proofs, etc. [ABSTRACT FROM AUTHOR]

The focus of this study is on the A+B transportation procurement mechanism, which uses the proposed cost (A component) and the proposed time (B component) to score contractors' bids. Empirical studies have shown that this mechanism shortens project durations. We use normative models to study the effect of certain discretionary parameters set by state transportation agencies on contractors' equilibrium bidding strategies, winner selection, and actual completion times. We model the bidding environment in detail including multi-dimensional bids, contractors' uncertainty about completion times, and reputation cost. The latter refers to a private penalty that accrues to tardy contractors from increased cost of posting bonds and reduced prospects of winning future projects. Our model explains why contractors may skew line-item bids and why winners frequently finish earlier than bid. It has several policy implications as well. For example, we recommend that agencies set the daily incentive, disincentive, and road user cost to be equal and not cap incentives. This is a departure from current practice, where incentives are often capped and weaker than penalties. Furthermore, we show that agencies may be justified in setting daily road user cost strictly smaller than the true cost of traffic disruption during construction. [ABSTRACT FROM AUTHOR]

In patient staffing costs are significantly affected by nurse absenteeism, which is typically high in U.S. hospitals. We use data from multiple inpatient units of two hospitals to study which factors, including unit culture, short-term workload, and shift type, explain nurse absenteeism. The analysis highlights the importance of paying attention to heterogeneous absentee rates among individual nurses. We then develop models to investigate the impact of demand and absentee rate variability on the performance of staffing plans and obtain some structural results. Utilizing these results, we propose and test three easy-to-use heuristics to identify near-optimal staffing strategies. Such strategies could be useful to hospitals that periodically reassign nurses with similar qualifications to inpatient units in order to balance workload and accommodate changes in patient flow. Although motivated by staffing of hospital inpatient units, the approach developed in this paper is also applicable to other team-based and labor-intensive service environments. [ABSTRACT FROM AUTHOR]

Supply disruptions are all too common in supply chains. To mitigate delivery risk, buyers may either source from multiple suppliers or offer incentives to their preferred supplier to improve its process reliability. These incentives can be either direct (investment subsidy) or indirect (inflated order quantity). In this study, we present a series of models to highlight buyers' and suppliers' optimal parameter choices. Our base-case model has deterministic buyer demand and two possibilities for the supplier yield outcomes: all-or-nothing supply or partial disruption. For the all-or-nothing model, we show that the buyer prefers to only use the subsidy option, which obviates the need to inflate order quantity. However, in the partial disruption model, both incentives-subsidy and order inflation-may be used at the same time. Although single sourcing provides greater indirect incentive to the selected supplier because that avoids order splitting, we show that the buyer may prefer the diversification strategy under certain circumstances. We also quantify the amount by which the wholesale price needs to be discounted (if at all) to ensure that dual sourcing strategy dominates sole sourcing. Finally, we extend the model to the case of stochastic demand. Structural properties of ordering/subsidy decisions are derived for the all-or-nothing model, and in contrast to the deterministic demand case, we establish that the buyer may increase use of subsidy and order quantity at the same time. [ABSTRACT FROM AUTHOR]

Carriers (airlines) use medium-term contracts to allot bulk cargo capacity to forwarders who deliver consolidated loads for each flight in the contractual period (season). Carriers also sell capacity to direct-ship customers on each flight. We study capacity contracts between a carrier and a forwarder when certain parameters such as the forwarder's demand, operating cost to the carrier, margin, and reservation profit are its private information. We propose contracts in which the forwarder pays a lump sum in exchange for a guaranteed capacity allotment and receives a refund for each unit of unused capacity according to a pre-announced refund rate. We obtain an upper bound on the informational rent paid by the carrier for a menu of arbitrary allotments and identify conditions under which it can eliminate the informational rent and induce the forwarder to choose the overall optimal capacity allotment (i.e., one that maximizes the combined profits of the carrier and the forwarder). [ABSTRACT FROM AUTHOR]

Merger and acquisition activity has increased sharply in the last decade. It seems useful to have models that can help senior managers of bidder firms make informed decisions about the amount of premium, over the target's share prices prevailing prior to merger announcement, that can be justified on the basis of operational synergies. The goal of this article is to capture important parameters from the production side that have a bearing on the valuation of the target's shares. We show that the production characteristics of both the bidder and the target matter in a significant way. For example, if the bidder and target operate in independent markets, the bidder has flexible production facilities but the target's production facilities are inflexible, then an increase in the bidder's demand can make the target less attractive and lower the value of operational synergy. [ABSTRACT FROM AUTHOR]

This paper considers the control of a single-server tandem queueing system with setups. Jobs arrive to the system according to a Poisson process and are produced to order. A single server must perform a number of different operations on each job. There is a setup time for the server to switch between different operations. We assume that there is a holding cost at each operation, which is nondecreasing in operation number (i.e., as value is added to a job, it becomes more expensive to hold). The control problem is to decide which job the server should process at each point in time.We formulate this control problem as a Markov-Decision Process. We partially characterize the optimal policy, develop an exact analysis of exhaustive and gated polling policies, and develop an effective heuristic policy. The results of a simulation study, which tests the performance of the policies considered, are reported. These computational results indicate that our heuristic is effective for a wide variety of cases. [ABSTRACT FROM AUTHOR]

This paper examines the impact on operating costs of having an unreliable supplier in a continuous review, fixed order quantity (Q) — reorder point (r) inventory system. We assume Poisson demand and exponentially distributed lengths of the supplier's on and off periods. On (off) periods represent time lengths during which the supplier is able (unable) to fill new orders. Any unsatisfied demand is assumed to be lost. We analyze two situations. The first has a negligible lead time but allows the number of outstanding orders, each of a fixed size Q, to be arbitrary. The second situation, on the other hand, has a constant lead time but there the number of outstanding orders is restricted to at most one. In each case, exact expressions necessary to find the average cost minimizing (Q, r) pair are developed and several numerical examples are solved. Computational results show the cost function to be well behaved and-suggest that ignoring supply uncertainty or approximate modeling can be relatively very expensive, especially when the off periods are long or shortage penalty is high or both. We also identify regions where the average operating cost associated with the computationally simpler approximate solution is not far from its optimum value. [ABSTRACT FROM AUTHOR]

When polling systems are used to model real-world systems, it is typically assumed that the server switches continuously ("roves") even when there are no waiting jobs in the system. However, requiring the server to be patient, instead of having it rove, might be more realistic. Furthermore, operational control of these systems can be improved by knowing answers to questions like "under what circumstances should a roving server be patient?" and "at which stations?". This paper analyzes the patient server model and provides explicit expressions for the waiting time distributions, the mean waiting times and the pseudo-conservation law. Several variants of the patient server model are considered. We show that while the patient server mechanism is generally better than the roving server mechanism in the work-in-process (WIP) reduction sense, there do exist cases where roving is better. Counter-intuitive examples where reducing switchover time can increase WIP are also reported. [ABSTRACT FROM AUTHOR]

This work concerns the advance scheduling of elective surgery when the operating rooms' capacity utilization by emergency surgery, as well as by elective procedures, is uncertain. New requests for bookings of elective surgery arrive each day. Such procedures preferably would be performed as soon as possible, but admitting too many patients may result in exceeding a day's capacity, possibly necessitating turning away some emergency cases. So the problem facing the hospital at the start of each day is how many of the additional requests for elective surgery to assign for that day. We provide a stochastic dynamic programming model for this aggregate advance scheduling problem. The model has some novel mathematical features. We analyze it and characterize the nature of the optimal policy, which is not necessarily of a control- limit type. Plausible numerical examples which confirm our theoretical results and provide additional insights are reported. [ABSTRACT FROM AUTHOR]

Introduction: Kidney transplant recipients expect to survive the procedure with sufficient renal function for reliable dialysis freedom., Methods: Transplant outcomes (survival and estimated renal function) were assessed after live and deceased donor transplantation from the US national database. Outcomes were stratified by age (donor and recipient) and donor type., Results: Aggregate recipient outcomes were better transplanting living vs deceased donated kidneys. However, when stratified by the one-year renal function (within KDIGO CKD stage stratifications), surviving recipients had clinically similar dialysis-freedom, irrespective of donor type or age. The major outcome differences for recipients of age-stratified live and deceased kidneys was 1) the increasing frequency of one-year graft failures and 2) the increasing likelihood of severely limited renal function (CKD 4/5) with advancing donor age. Over 30% of recipients of deceased kidneys >65 years had either one-year graft failure or severely limited renal function contrasted to less than 15% of recipients of live kidneys aged >65 years., Conclusions: Evolving techniques to reduce adverse events after urgent vs elective procedures, plus improved transplant outcome predictability with increased-age deceased donor kidneys using advanced predictive analytics (using age-stratified live kidney transplantation outcomes as a relevant reference point) should facilitate similar kidney transplant outcomes, irrespective of donor type., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Pruett, Martin and Gupta.)

Operating rooms (ORs) in US hospitals are costly to staff, generate about 70 % of a hospital's revenues, and operate at a staffed-capacity utilization of 60-70 %. Many hospitals allocate blocks of OR time to individual or groups of surgeons as guaranteed allocation, who book surgeries one at a time in their blocks. The booking procedure frequently results in unused time between surgeries. Realizing that this presents an opportunity to improve OR utilization, hospitals manually reschedule surgery start times one or two days before each day of surgical operations. The purpose of rescheduling is to decrease OR staffing costs, which are determined by the number of concurrently staffed ORs. We formulate the rescheduling problem as a variant of the bin-packing problem with interrelated items, which are the surgeries performed by the same surgeon. We develop a lower bound (LB) construction algorithm and prove that the LB is at least (2/3) of the optimal staffing cost. A key feature of our approach is that we allow hospitals to have two shift lengths. Our analytical results form the basis of a branch-and-bound algorithm, which we test on data obtained from three hospitals. Experiments show that rescheduling saves significant staffing costs.

S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) link one-carbon metabolism to methylation status. However, it is unknown whether regulation of SAM and SAH by nutrient availability can be directly sensed to alter the kinetics of key histone methylation marks. We provide evidence that the status of methionine metabolism is sufficient to determine levels of histone methylation by modulating SAM and SAH. This dynamic interaction led to rapid changes in H3K4me3, altered gene transcription, provided feedback regulation to one-carbon metabolism, and could be fully recovered upon restoration of methionine. Modulation of methionine in diet led to changes in metabolism and histone methylation in the liver. In humans, methionine variability in fasting serum was commensurate with concentrations needed for these dynamics and could be partly explained by diet. Together these findings demonstrate that flux through methionine metabolism and the sensing of methionine availability may allow direct communication to the chromatin state in cells., (Copyright © 2015 Elsevier Inc. All rights reserved.)