O perating rooms (ORs) are the greatest source of revenues for hospitals and also their largest cost centers. When scheduling surgeries, hospitals face a trade-off between the need to conduct planned elective surgeries and the need to be responsive to emergency cases. However, scheduling ORs, especially at Level-1 trauma hospitals, is challenging due to significant uncertainties in the arrivals of patients requiring emergent surgery. The issue of allocating limited capacity to emergent surgery cases while scheduling elective patients has major policy implications. We develop a model for allocating the OR capacity to elective patients in such a way that the emergency patients who arrive randomly can be accommodated without incurring excessive delays. The objective is to develop a framework for aggregate weekly schedules and generate detailed daily schedules that minimize the total cost of the ORs' expected operating time, idle time, and overtime. We present optimization procedures for generating effective schedules and rescheduling procedures that adjust the schedules of elective patients affected by emergency arrivals. Initially, the procedures assume deterministic surgery times for elective patients; the procedures are then extended to include stochastic surgery times. We show that for a given arrival rate of emergency patients, the total expected cost is convex in the weekly load of elective surgeries being scheduled. Numerical experiments are devised to obtain total expected cost curves for various emergency arrival rates. Using these curves, the optimal capacity allocation of ORs to elective patients can be determined as a function of the emergency arrival rate.

W e consider the stochastic, single-machine earliness/tardiness problem (SET), with the sequence of processing of the jobs and their due-dates as decisions and the objective of minimizing the sum of the expected earliness and tardiness costs over all the jobs. In a recent paper, Baker (2014) shows the optimality of the Shortest-Variance-First (SVF) rule under the following two assumptions: (a) The processing duration of each job follows a normal distribution. (b) The earliness and tardiness cost parameters are the same for all the jobs. In this study, we consider problem SET under assumption (b). We generalize Baker's result by establishing the optimality of the SVF rule for more general distributions of the processing durations and a more general objective function. Specifically, we show that the SVF rule is optimal under the assumption of dilation ordering of the processing durations. Since convex ordering implies dilation ordering (under finite means), the SVF sequence is also optimal under convex ordering of the processing durations. We also study the effect of variability of the processing durations of the jobs on the optimal cost. An application of problem SET in surgical scheduling is discussed.

This article considers the problems of scheduling operations in single-gripper and dual-gripper bufferless robotic cells in which the arrangement of machines is circular. The cells are designed to produce identical parts under the free-pickup criterion with additive intermachine travel time. The objective is to find a cyclic sequence of robot moves that minimizes the long-run average time required to produce a part or, equivalently, that maximizes the throughput. Obtaining an efficient algorithm for an approximation to an optimal k-unit cyclic solution (over all k≥ 1) is the focus of this article.The proposed algorithms introduce a new class of schedules, which are refered to as epi-cyclic cycles. A polynomial algorithm with a 5/3-approximation to an optimal k-unit cycle over all cells is developed. The performed structural analysis for dual-gripper cells leads to a polynomial-time algorithm that provides at worst a 3/2-approximation for the practically relevant case in which the dual-gripper switch time is less than twice the intermachine robot movement time. A computational study demonstrates that the algorithm performs much better on average than this worst-case bound suggests. The performed theoretical studies are a stepping stone for researching the complexity status of the corresponding domain. They also provide theoretical as well as practical insights that are useful in maximizing productivity of any cell configuration with either type of robot.

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The effect of pressure up to 5.6 CPa on the magnetic behaviour of y'-FqN has been investigated using the 57Fe high-pressure Miissbauer effect technique at 300 K. We show that the decrease of the average magnetic hyperfine held at 300 K in this pressure range results from the decreases of the Fe local magnetic moment and Curie temperature with pressure. The decreases of the average isomer shift and the isomer shin for each Fe site with increasing pressure indicates a corresponding increase of s electron density at the "Fe nucleus, which is mainly caused by the volume compression of the 4s conduction electrons and changes of charge innsfer behveen atoms.

Sales on the e-commerce platform in the United States have experienced explosive growth and are projected to surpass $740 billion in 2023. The expansion of the platform’s traditional role as a reseller into an online marketplace and the introduction of its own brand products have stoked a huge fear among the incumbent sellers. The platform’s unfair anti-competitive practice further aggravates the situation. Consequently, politicians and regulators have proposed prohibiting platforms from introducing own brand products to protect the incumbent sellers. This study addresses two questions of critical interest to the policymakers and the incumbent sellers. First, how does the platform’s introducing its own brand product affect the incumbent sellers? Second, how effective is the proposed policy in terms of protecting the incumbent sellers? We examine the impact of the platform’s own brand introduction on the incumbent sellers under two prevailing sell-on and sell-to pricing contracts. We find that the proposed legislation “that prohibits platforms from both offering a marketplace for commerce and participating in that marketplace” does not have the desired outcome of helping the incumbent sellers. Instead, it forces the platform to adopt only the sell-to contract with its own brand introduction which hurts the sellers under most market conditions.

M any automated manufacturing systems use robotic cells, which consist of a set of machines served by a robot.Robotic cells with a single-gripper robot have been extensively studied in the literature. By contrast, cells with a dual-gripper robot, although more productive, have received less attention, perhaps because of their inherent complexity. We consider the problem of scheduling operations in dual-gripper robotic cells that have the machines configured in a circular layout and that produce identical parts repetitively. A typical objective in practice is to find a 1-unit cyclic sequence of robot moves that maximizes the throughput. We show that dual-gripper cycles are not optimal in all cases. We establish conditions in which the problem of finding an optimal 1-unit cycle in dual-gripper cells is NP-hard. We show that the remaining cases are solvable by polynomial-time algorithms either optimally or within a guaranteed bound of the optimum. These results are extended to linear cells. A computational study demonstrates that the algorithm performs much better on average than this worst-case bound suggests. Our theoretical studies facilitate research into the complexity status of the corresponding domain. They also provide practical insights that are useful in maximizing productivity for any combination of cell parameters and either type of robot.Notes. P, polynomially solvable; NPHO, NP-Hard in the ordinary sense. *Best known approximation bounds are given in square brackets.

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