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Competitive solutions for online financial problems
 ACM Comput. Surv
, 1998
"... This article surveys results concerning online algorithms for solving problems related to the management of money and other assets. In particular, the survey focuses on search, replacement, and portfolio selection problems. ..."
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This article surveys results concerning online algorithms for solving problems related to the management of money and other assets. In particular, the survey focuses on search, replacement, and portfolio selection problems.
Nearly Optimal Competitive Online Replacement
"... This paper studies the following online replacement problem. There is a real function f(t), called the flow rate, defined over a finite time horizon [0; T ]. It is known that m f(t) M for some reals 0 m ! M . At time 0 an online player starts to pay money at the rate f(0). At each time 0 ! t T ..."
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This paper studies the following online replacement problem. There is a real function f(t), called the flow rate, defined over a finite time horizon [0; T ]. It is known that m f(t) M for some reals 0 m ! M . At time 0 an online player starts to pay money at the rate f(0). At each time 0 ! t T the player may changeover and continue paying money at the rate f(t). The complication is that each such changeover incurs some fixed penalty. The player is called online as at each time t the player knows f only over the time interval [0; t]. The goal of the player is to minimize the total cost comprised of cumulative payment flow plus changeover costs. This formulation of the replacement problem has various interesting applications among which are: equipment replacement, supplier replacement, the menu cost problem and mortgage refinancing.
Optimal Joint Preventive Maintenance and Production Policies*
, 2005
"... Abstract: We study joint preventive maintenance (PM) and production policies for an unreliable productioninventory system in which maintenance/repair times are nonnegligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to pro ..."
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Abstract: We study joint preventive maintenance (PM) and production policies for an unreliable productioninventory system in which maintenance/repair times are nonnegligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to produce. We consider a discretetime system, formulating the problem as a Markov decision process (MDP) model. The focus of the work is on the structural properties of optimal joint policies, given the system state comprised of the system’s age and the inventory level. Although our analysis indicates that the structure of optimal joint policies is very complex in general, we are able to characterize several properties regarding PM and production, including optimal production/maintenance actions under backlogging and high inventory levels, and conditions under which the PM portion of the joint policy has a controllimit structure. In further special cases, such as when PM setup costs are negligible compared to PM
OPTIMALITY OF CONTROL LIMIT MAINTENANCE POLICIES UNDER NONSTATIONARY DETERIORATION
 PROBABILITV IN THE ENGINEERING AND INFNRMATIONAL SCIENCES,13, 1999,5570. PRINTED IN THE U.S.A.
, 1999
"... Control limit type policies are widely discussed in the literature, particularly regarding the maintenance of deteriorating systems. Previous studies deal mainly with stationary deterioration processes, where costs and transition probabilities depend only on the state of the system, regardless of it ..."
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Control limit type policies are widely discussed in the literature, particularly regarding the maintenance of deteriorating systems. Previous studies deal mainly with stationary deterioration processes, where costs and transition probabilities depend only on the state of the system, regardless of its cumulative age. In this paper, we consider a nonstationary deterioration process, in which operation and maintenance costs, as well as transition probabilities "deteriorate " with both the system's state and its cumulative age. We discuss conditions under which control limit policies are optimal for such processes and compare them with thclse used in the analysis of stationary models. Two maintenance models are examined: in the first (as in the majority of classic studies), the only maintenance action allowed is the replacement of the system by a new one. In this case, we show that the nonstationary results are direct generalizations of their counterparts in stationary models. We propose an efficient algorithm for finding the optimal policy, utilizing its control limit form. In the second model we also allow for repairs to better states (without changing the age). In this case, the optimal policy is shown to have the form of a 3way control limit rule. However, conditions analogous to those used in the stationary problem do not suffice, so additional, more restrictive ones are suggested and discussed.
Health Care Manage Sci (2007) 10:81–93 DOI 10.1007/s1072900690072 Safetycost tradeoffs in medical device reuse: a Markov decision process model
"... Abstract Healthcare expenditures in the US are approaching $2 trillion, and hospitals and other healthcare providers are under tremendous pressure to rein in costs. One costsaving approach which is gaining popularity is the reuse of medical devices which were designed only for a single use. Devic ..."
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Abstract Healthcare expenditures in the US are approaching $2 trillion, and hospitals and other healthcare providers are under tremendous pressure to rein in costs. One costsaving approach which is gaining popularity is the reuse of medical devices which were designed only for a single use. Device makers decry this practice as unsanitary and unsafe, but a growing number of thirdparty firms are willing to sterilize, refurbish, and/or remanufacture devices and resell them to hospitals at a fraction of the original price. Is this practice safe? Is reliance on singleuse devices sustainable? A Markov decision process (MDP) model is formulated to study the tradeoffs involved in these decisions. Several key parameters are examined: device costs, device failure probabilities, and failure penalty cost. For each of these parameters, expressions are developed which identify the indifference point between using new and reprocessed devices. The results can be used to inform the debate on the economic, ethical, legal, and environmental dimensions of this complex issue.
OPTIMAL POLICIES FOR THE ACCEPTANCE OF LIVING AND
, 2004
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Abstract Production, Manufacturing and Logistics Technological advancement, learning, and the adoption of new technology
, 2002
"... This research focuses attention upon three related issues: the persistence of technological progress over time, multiple adoption decisions over a long horizon, and the impact of production based learning on those decisions. We develop a simple economic model for a single product producing firm inco ..."
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This research focuses attention upon three related issues: the persistence of technological progress over time, multiple adoption decisions over a long horizon, and the impact of production based learning on those decisions. We develop a simple economic model for a single product producing firm incorporating continuous technological progress, linear product demand, linear switching costs, and experience based cost reductions. A dynamic programming framework is used to evaluate cases where either one or an unlimited number of adoptions are allowed over an infinite horizon. Both structural and numerical results are presented. Fundamental results serve to explain several counterintuitive dynamics. In the single adoption case, faster rates of technological progress, as well as growing markets, or a steeply sloping demand curve, serve to delay adoption while an increased ability to learn may accelerate it. When multiple adoptions are allowed, the adoption of any particular technology presents a ‘‘window of opportunity’ ’ in which future investment will be warranted. If, for whatever reason, this window has passed, then maintaining the older technology becomes more attractive than adoption. Thus, seemingly outdated technologies may remain embedded in some settings. Ó 2002 Elsevier B.V. All rights reserved.
Stochastics and Statistics A preventive maintenance policy with sequential checking procedure for a Markov deteriorating system
, 1999
"... We consider a repairable system subject to a continuoustime Markovian deterioration while running, that leads to failure. The deterioration degree is measured with a finite discrete scale; repairs follow general distributions; failures are instantaneously detected. This system is submitted to a pre ..."
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We consider a repairable system subject to a continuoustime Markovian deterioration while running, that leads to failure. The deterioration degree is measured with a finite discrete scale; repairs follow general distributions; failures are instantaneously detected. This system is submitted to a preventive maintenance policy, with a sequential checking procedure: the upstates are divided into two parts, the ‘‘good’ ’ upstates and the ‘‘degraded’ ’ upstates. Instantaneous (and perfect) inspections are then performed on the running system: when it is found in a degraded upstate, it is stopped to be maintained (for a random duration that depends on the degradation degree of the system); when it is found in a good upstate, it is left as it is. The next inspection epoch is then chosen randomly and depends on the degradation degree of the system by time of inspection. We compute the longrun availability of the maintained system and give sufficient conditions for the preventive maintenance policy to improve the longrun availability. We study the optimization of the longrun availability with respect to the distributions of the interinspection intervals: we show that under specific assumptions (often checked), optimal distributions are nonrandom. Numerical examples are studied.
Repeat Purchase Decisions under Sequential Innovation
, 2003
"... Improving technologies create a “buy or wait? ” dilemma. In this paper, we consider repeat purchases when the consumer faces an infinite stream of new technologies. We develop a probabilistic model and focus on the role of “more variability ” on the process of technological innovation. Similar to r ..."
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Improving technologies create a “buy or wait? ” dilemma. In this paper, we consider repeat purchases when the consumer faces an infinite stream of new technologies. We develop a probabilistic model and focus on the role of “more variability ” on the process of technological innovation. Similar to real options models, we find that variability in the technological process increases value for the consumer. Unlike other results we have seen, more variability lowers the optimal threshold. Using the monotonicity of the strategy in variability, we derive upper and lower bounds on the critical threshold.
©2007 INFORMS Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List
"... doi 10.1287/opre.1060.0329 ..."