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Staff assignment policies for a mass casualty event queuing network

ANNALS OF OPERATIONS RESEARCH 2019年第1-2期283卷 411-442页

作者： Lodree, Emmett J. Altay, Nezih Cook, Robert A. Univ Alabama Culverhouse Coll Commerce & Business Adm Tuscaloosa AL 35487 USA Depaul Univ Driehaus Coll Business Chicago IL 60604 USA

We study parallel queuing systems in which heterogeneous teams collaborate to serve queues with three different prioritization levels in the context of a mass casualty event. We assume that the health condition of casualties deteriorate as time passes and aim to minimize total deprivation cost in the system. Servers (i.e. doctors and nurses) have random arrival rates and they are assigned to a queue as soon as they arrive. While nurses and doctors serve their dedicated queues, collaborative teams of doctors and nurses serve a third type of customer, the patients in critical condition. We model this queueing network with flexible resources as a discrete-time finite horizon stochastic dynamic programming problem and develop heuristic policies for it. Our results indicate that the standard c mu rule is not an optimal policy, and that the most effective heuristic policy found in our simulation study is intuitive and has a simple structure: assign doctor/nurse teams to clear the critical patient queue with a buffer of extra teams to anticipate future critical patients, and allocate the remaining servers among the other two queues.

关键词： Humanitarian logistics Medical emergency stochastic dynamic programming Monte Carlo simulation

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Analysis of the privacy-performance tradeoff of reference testing in Forensic Investigative Genetic Genealogy

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JOURNAL OF FORENSIC SCIENCES 2024年第5期69卷 1699-1705页

作者： Hu, Yuchen Wein, Lawrence M. Stanford Univ Dept Management Sci & Engn Stanford CA USA Stanford Univ Grad Sch Business Stanford CA 94305 USA

During an investigation using Forensic Investigative Genetic Genealogy, which is a novel approach for solving violent crimes and identifying human remains, reference testing-when law enforcement requests a DNA sample from a person in a partially constructed family tree-is sometimes used when an investigation has stalled. Because the people considered for a reference test have not opted in to allow law enforcement to use their DNA profile in this way, reference testing is viewed by many as an invasion of privacy and by some as unethical. We generalize an existing mathematical optimization model of the genealogy process by incorporating the option of reference testing. Using simulated versions of 17 DNA Doe Project cases, we find that reference testing can solve cases more quickly (although many reference tests are required to substantially hasten the investigative process), but only rarely (<1%) solves cases that cannot otherwise be solved. Through a mixture of mathematical and computational analysis, we find that the most desirable people to test are at the bottom of a path descending from an ancestral couple that is most likely to be related to the target. We also characterize the rare cases where reference testing is necessary for solving the case: when there is only one descending path from an ancestral couple, which precludes the possibility of identifying an intersection (e.g., marriage) between two descendants of two different ancestral couples.

关键词： family trees forensic genetic genealogy performance analysis privacy probabilistic analysis stochastic dynamic programming

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Operational planning of distributed energy generation for a semiconductor fabrication plant

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ELEKTROTECHNIK UND INFORMATIONSTECHNIK 2022年第8期139卷 662-672页

作者： Poemsl, Tobias F. Siddiqui, Afzal S. Stockholm Univ Dept Comp & Syst Sci Borgarfjordsgatan 12 S-16407 Kista Sweden Aalto Univ Dept Math & Syst Anal Aalto Finland

The semiconductor industry is well known for its high resource consumption due to its clean room usage and power-intensive manufacturing technology. This is a significant financial burden for semiconductor fabrication plant owners who wish to minimize the cost needed to cover the electricity and gas loads for their daily operations. From a historical perspective, those electricity and gas cost reductions have been enabled by more energy-efficient manufacturing technologies. Due to the complexity of factors influencing the energy system of a semiconductor plant, other aspects have often been neglected and also not been studied intensively in the academic literature so far. One possibility for reducing energy costs is the integration of a microgrid as on-site distributed energy resources (DER) may offer a less cost-intensive way to supply the energy needed. Therefore, this paper seeks to answer the following research question: How much expected cost can be saved and risk mitigated at a semiconductor fabrication plant via DER? More precisely, in this paper, a microgrid at a semiconductor fabrication plant that has installed DER with combined heat and power (CHP) applications and demand response (DR) is used to simulate the expected annual energy costs under given uncertain electricity and gas prices at different installed capacity levels. A simulation-based approach is used to evaluate several DER capacity sizes. The results of the simulation show that installations of DER at a semiconductor microgrid can dominate the base case of doing nothing, considering the expected minimized cost, the expected CO2 emissions, and conditional value-at-risk (CVaR). In fact, DER can reduce the expected annual energy bill by up to 6%, whereas annual expected CO2 emissions can even be reduced by up to 22%. Moreover, with DER, a microgrid's risk is reduced as it can react to market conditions and local demand. Additionally, the true potential of microgrid cost savings can only be enabled

关键词： Microgrids Simulation Operational planning Energy system optimization Distributed energy resources stochastic dynamic programming

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Optimal management of DC pension plan in a stochastic interest rate and stochastic volatility framework

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INSURANCE MATHEMATICS & ECONOMICS 2014年第1期57卷 58-66页

作者： Guan, Guohui Liang, Zongxia Tsinghua Univ Dept Math Sci Beijing 100084 Peoples R China

This paper investigates an optimal investment strategy of DC pension plan in a stochastic interest rate and stochastic volatility framework. We apply an affine model including the Cox-Ingersoll-Ross (CIR) model and the Vasicek mode to characterize the interest rate while the stock price is given by the Heston's stochastic volatility (SV) model. The pension manager can invest in cash, bond and stock in the financial market. Thus, the wealth of the pension fund is influenced by the financial risks in the market and the stochastic contribution from the fund participant. The goal of the fund manager is, coping with the contribution rate, to maximize the expectation of the constant relative risk aversion (CRRA) utility of the terminal value of the pension fund over a guarantee which serves as an annuity after retirement. We first transform the problem into a single investment problem, then derive an explicit solution via the stochastic programming method. Finally, the numerical analysis is given to show the impact of financial parameters on the optimal strategies. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Defined contribution pension plan CRRA utility stochastic dynamic programming stochastic interest rate stochastic volatility stochastic contribution rate Minimum guarantee

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THE SEARCH FOR INFORMATION - A PATIENT PERSPECTIVE ON MULTIPLE OPINIONS

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1995年第2期85卷 244-262页

作者： MEHREZ, A YUAN, Y GAFNI, A MCMASTER UNIV CTR HLTH ECON & POLICY ANALDEPT CLIN EPIDEMIOL & BIOSTATHAMILTONON L8N 3Z5CANADA MCMASTER UNIV MICHAEL G DEGROOTE SCH BUSINESSHAMILTONON L8S 4M4CANADA KENT STATE UNIV GRAD SCH MANAGEMENTKENTOH 44242 MCMASTER UNIV CTR HLTH ECON & POLICY ANALHAMILTONON L8N 3Z5CANADA

This paper describes the first dynamic formulation of the optimal strategy, from a patient perspective, for the search for additional information in the form of multiple opinions. The Mehrez and Gafni framework for choosing an optimal treatment from a patient perspective is employed to study the optimal search strategy for a representative individual who is an expected utility maximizer. Two different processes for gathering information regarding the probability of treatment success (P) are studied: In the first, physicians provide information in a yes or no (treatment) type of recommendation;in the second, physicians provide probabilistic information about the likelihood of success in the treatment. For the first system the optimal strategy is derived using an algorithm of an order O(n) (n is the number of opinions to be purchased from expert doctors) for a prior beta probability density function of P and a Bernoulli process of information gathering. EVSI (expected value of sample information) measures are incorporated into the Bayesian analysis to study this case and to obtain an upper bound on n* (the optimal number of opinions to be purchased). The approach developed here is different than the well known one provided by Raiffa and Schlaifer in 1961 and it enables us to present additional results regarding the optimal search strategy and how to identify it. For example, if (i) the process of information gathering is generated by a Bernoulli process, (ii) the natural conjurate prior distribution is beta, and (iii) the utility functions are linear functions of the probability of treatment success, then for each n, there exists at most one value of x (the number of experts recommending treatment) for which a search should continue. At this value the incremental increase of the individual's lifetime expected utility stemming from the decision to seek additional expert's opinion is positive. This observation might explain a reality where the likelihood of seeking a la

关键词： stochastic dynamic programming EXPECTED VALUE OF SAMPLE INFORMATION (EVSI) 2ND OPINION

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Category count models for adaptive management of metapopulations: Case study of an imperiled salamander

CONSERVATION SCIENCE AND PRACTICE

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CONSERVATION SCIENCE AND PRACTICE 2020年第4期2卷 1-13页

作者： O'Donnell, Katherine M. Fackler, Paul L. Johnson, Fred A. Bonneau, Mathieu N. Martin, Julien Walls, Susan C. US Geol Survey Wetland & Aquat Res Ctr 7920 NW 71st St Gainesville FL 32653 USA North Carolina State Univ Dept Agr & Resource Econ Raleigh NC USA Univ Florida Dept Wildlife Ecol & Conservat Gainesville FL USA US Geol Survey St Petersburg Coastal & Marine Sci Ctr St Petersburg FL USA INRA Unite Recherches Zootech URZ F-97170 Petit Bourg Guadeloupe France

Managing spatially structured populations of imperiled species presents many challenges. Spatial structure can make it difficult to predict population responses to potential recovery activities, and learning through experimentation may not be advised if it could harm threatened populations. Adaptive management provides an appealing framework when experimentation is considered too risky or time consuming;we used such an approach for imperiled flatwoods salamanders at a Florida wildlife refuge. We represented this metapopulation with category count models and used stochastic dynamic programming to identify optimal decision policies that weighed trade-offs between metapopulation persistence and management costs. We defined possible wetland categories in terms of habitat suitability and occupancy, specified category-specific management actions, and identified transition probabilities via expert elicitation for two management strategies: "future" status quo (FSQ;frequent growing-season burns) and extra management actions (EMA;restoration, translocation, head-starting). We simulated metapopulation dynamics using the resulting optimal management policy and found that under model FSQ, occupancy steadily declined over time, indicating that populations would rapidly become extirpated;with model EMA, occupancy remained stable, suggesting that populations would persist only if additional actions are applied and are effective. This approach can be used to identify optimal solutions while accounting for uncertainty and considering both habitat and population dynamics, and to help managers make conservation decisions for populations at imminent risk of extinction.

关键词： adaptive management Ambystoma amphibian decision analysis endangered species flatwoods salamander Markov decision process stochastic dynamic programming

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stochastic Control for Optimal Execution:Fast Approximation Solution Scheme Under Nested Mean-semi Deviation and Conditional Value at Risk

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Journal of the Operations Research Society of China 2017年第2期5卷 161-176页

作者： Meng-Fei He Duan Li Yuan-Yuan Chen China International Fund Management Ltd Shanghai 200120China Department of Systems Engineering and Engineering Management The Chinese University of Hong KongHong KongChina Risk Management Institute National University of SingaporeSingaporeSingapore

When executing a large order of stocks in a market,one important factor in forming the optimal trading strategy is to consider the price impact of large-volume trading *** a risk measure of the implementation shortfall,i.e.,the difference between the value of a trader’s initial equity position and the sum of cash flow he receives from his trading process,is essentially a stochastic control *** this study,we investigate such a practical problem under a dynamic coherent risk measure in a market in which the stock price dynamics has a feature of momentum *** develop a fast approximation solution scheme,which is critical in highfrequency *** demonstrate some prominent features of our derived solution algorithm in providing useful guidance for real implementation.

关键词： Nested coherent risk measure Momentum effect Approximation solution scheme stochastic dynamic programming

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Welfare Implications of Water Scarcity: Higher Prices of Desalination

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ENVIRONMENTAL & RESOURCE ECONOMICS 2019年第4期73卷 995-1022页

作者： Saglam, Yigit Victoria Univ Wellington Sch Econ & Finance POB 600 Wellington 6140 New Zealand

In this paper, we evaluate the welfare implications of shortages in renewable resources, and investigate the effects of cross-subsidization on these shortages. We set up a stochastic dynamic programming model in which a benevolent supplier allocates the resource for multiple user groups subject to revenue and resource constraints. The supplier also has access to an external source that can be utilized at a certain cost. The solution to the model gives the optimal sectoral prices, and demand for the external source. We find out that saving budget surplus during periods of scarcity allows the planner to charge prices below average costs when the resource is abundant. Using data from Turkey, we simulate our dynamic model to quantify the implications of cross-subsidization on water use across user groups.

关键词： Renewable resource Water shortages stochastic dynamic programming Desalination Cross-subsidization

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The optimal harvesting problem under price uncertainty

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ANNALS OF OPERATIONS RESEARCH 2014年第1期217卷 425-445页

作者： Piazza, Adriana Pagnoncelli, Bernardo K. Univ Tecn Federico Santa Maria Dept Matemat Valparaiso Chile Univ Adolfo Ibanez Escuela Negocios Santiago Chile

In this paper we study the exploitation of a one species forest plantation when timber price is governed by a stochastic process. The work focuses on providing closed expressions for the optimal harvesting policy in terms of the parameters of the price process and the discount factor, with finite and infinite time horizon. We assume that harvest is restricted to mature trees older than a certain age and that growth and natural mortality after maturity are neglected. We use stochastic dynamic programming techniques to characterize the optimal policy and we model price using a geometric Brownian motion and an Ornstein-Uhlenbeck process. In the first case we completely characterize the optimal policy for all possible choices of the parameters. In the second case we provide sufficient conditions, based on explicit expressions for reservation prices, assuring that harvesting everything available is optimal. In addition, for the Ornstein-Uhlenbeck case we propose a policy based on a reservation price that performs well in numerical simulations. In both cases we solve the problem for every initial condition and the best policy is obtained endogenously, that is, without imposing any ad hoc restrictions such as maximum sustained yield or convergence to a predefined final state.

关键词： stochastic dynamic programming Forest management Optimal harvesting Price uncertainty

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A dynamic inventory rationing problem with uncertain demand and production rates

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ANNALS OF OPERATIONS RESEARCH 2015年第1期231卷 207-228页

作者： Turgay, Zeynep Karaesmen, Fikri Ormeci, E. Lerzan Koc Univ Dept Ind Engn Istanbul Turkey

We investigate the structural properties of a finite horizon, discrete time single product inventory rationing problem, where we allow random replenishment (production) opportunities. In contrast to the standard models of dynamic capacity control in revenue management or production/inventory systems, we assume that the demand/production rates are not known with certainty but lie in some interval. To address this uncertainty, we formulate a robust stochastic dynamic program and show how the structural properties of the optimal policy propagate to the robust counterpart of the problem. Further, we explore how the optimal policy changes with respect to the uncertainty set. We also show that our results can be extended to certain alternative robust formulations.

关键词： Inventory control stochastic dynamic programming Robust formulations

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