Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.     

Note: Open-shop scheduling with release dates to minimize maximum lateness

We present the first polynomial-time algorithm for an open-shop problem with unit execution times, arbitrary release dates, and due dates. The objective is to minimize maximum lateness. © 1995 John Wiley & Sons, Inc.     

Simultaneous determination of production and maintenance schedules using in‐line equipment condition and yield information

In many manufacturing environments, equipment condition has a significant impact on product quality, or yield. This paper presents a semi‐Markov decision process model of a single‐stage production system with multiple products and multiple maintenance actions. The model simultaneously determines maintenance and production schedules, accounting for the fact that equipment condition affects the yield of each product differently. It extends earlier work by allowing the expected time between decision epochs to vary by both action and machine state, by allowing multiple maintenance actions, and by treating the outcome of maintenance as less than certain. Sufficient conditions are developed that ensure the monotonicity of both the optimal production and maintenance actions. While the maintenance conditions closely resemble previously studied conditions for this type of problem, the production conditions represent a significant departure from earlier results. The simultaneous solution method is compared to an approach commonly used in industry, where the maintenance and production problems are treated independently. Solving more than one thousand test problems confirms that the combination of both features of the model—accounting for product differences and solving the problems simultaneously—has a significant impact on performance. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Damage functions and estimates of fratricide and collateral damage

There are multiple damage functions in the literature to estimate the probability that a single weapon detonation destroys a point target. This paper addresses differences in the tails of four of the more popular damage functions. These four cover the asymptotic tail behaviors of all monotonically decreasing damage functions with well‐behaved hazard functions. The differences in estimates of probability of kill are quite dramatic for large aim‐point offsets. This is particularly important when balancing the number of threats that can be engaged with the chances of fratricide and collateral damage. In general, analysts substituting one damage function for another may badly estimate kill probabilities in offset‐aiming, which could result in poor doctrine. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 306–321, 2003.     

Geopolitics over Proliferation: the Origins of US Grand Strategy and Their Implications for the Spread of Nuclear Weapons in South Asia

How much does the United States care about nonproliferation? Recent scholarship suggests that the fear of spreading nuclear weapons was central to the US grand strategy in the Cold War. In one important case, however, this argument does not hold. This article draws on theoretical debates and newly declassified archives to demonstrate the primacy of geopolitics over nonproliferation in Washington’s policy toward India and Pakistan. Despite their rhetoric, Democratic and Republican leaders consistently relegated nonproliferation to the backburner whenever it conflicted with other strategic goals. Moreover, they inadvertently encouraged proliferation in South Asia at three inter-connected levels: technology, security, and identity.     

Using real options analysis to value reoptimization options in the shifting bottleneck heuristic

The reoptimization procedure within the shifting bottleneck (SB) involves reevaluation of all previously scheduled toolgroup subproblems at each iteration of the SB heuristic. A real options analysis (ROA) model is developed to value the option to reoptimize in the SB heuristic, such that reoptimization only occurs when it is most likely to lead to a schedule with a lower objective function. To date, all ROA models have sought to value options financially (i.e., in terms of monetary value). The ROA model developed in this paper is completely original in that it has absolutely no monetary basis. The ROA methodologies presented are shown to greatly outperform both full and no reoptimization approaches with respect to both computation time and total weighted tardiness. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Impediments to Fighting the Islamic State: Private Contractors and US Strategy

The United States has returned to Iraq, this time to combat the Islamic State. President Barack Obama’s strategy to ‘degrade, and ultimately destroy the terrorist group’ faces serious problems due to political obstacles in obtaining Congressional Authorization for the Use of Military Force (AUMF) and more importantly because of neglect of the crucial role of private contractors. Although the narrative has changed, and there is no public mention of contractors, they remain central to all that the Department of Defense does in the US and abroad. Suggestions are offered on how their performance can be improved to support President Obama’s strategy.     

Minimal forecast horizon procedures for dynamic lot size models

This article presents new results which should be useful in finding production decisions while solving the dynamic lot sizing problem of Wagner–Whitin on a rolling horizon basis. In a rolling horizon environment, managers obtain decisions for the first period (or the first few periods) by looking at the forecasts for several periods. This article develops procedures to find optimal decisions for any specified number of initial periods (called planning horizon in the article) by using the forecast data for the minimum possible number of future periods. Computational results comparing these procedures with the other procedures reported in the literature are very encouraging.