Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 38 for “"Stochastic dynamic programming"”.
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Scheduling Policy Design using Stochastic Dynamic Programming
Scheduling policies for open soft real-time systems must be able to balance the competing concerns of meeting their objectives under exceptional conditions while achieving good performance in the average case. Balancing these concerns requires modeling strategies that represent the range of …
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Stochastic Dynamic Programming for Optimal Reservoir Control
… analyses were performed to examine typical stochastic programming (SP) modeling issues for a hypothetical single reservoir system. The elements considered in these analyses include the partitions of inflow and storage states, the hydrologic characteristics of inflows, the types of system …
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Optimizing loblolly pine management with stochastic dynamic programming
… with risk-adjusted discount rates, and a stochastic approach, where probability functions of cash flows are used to maximize expected utility from net present values. The stochastic approach is further divided into non-adaptive scenarios and adaptive scenarios, where the investor can …
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An application of stochastic dynamic programming to group revenue management
… pricing among other factors. In this thesis, a stochastic optimality control problem which consists of finding an optimal policy to when it is profitable (or not) to accept a group request is considered. A detailed review of the literature available on optimal inventory control is given in the …
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Computing policy parameters for stochastic inventory control using stochastic dynamic programming approaches
… inventory control policy parameters for the stochastic inventory control problem under Scarf’s setting. A common aspect of the solutions presented herein is the usage of stochastic dynamic programming approaches, a mathematical programming technique introduced by Bellman. Stochastic dynamic …
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Analyzing and Solving Non-Linear Stochastic Dynamic Models on Non-Periodic Discrete Time Domains
<p>Stochastic dynamic programming is a recursive method for solving sequential or multistage decision problems. It helps economists and mathematicians construct and solve a huge variety of sequential decision making problems in stochastic cases. Research on stochastic dynamic programming is …
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Optimal dynamic marketing strategies for grain producers: A case study of winter wheat
… optimal grain marketing decisions utilizing a stochastic dynamic programming framework. Consideration is given to the linkages, stochastic nature, and dynamics of income taxes, current grain market conditions, the financial condition of the firm, marketing constraints of the producer and …
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Dynamic Programming Model of the Corn Production Decision Process With Stochastic Climate Forecasts (Information, Illinois)
… (1) the need to model crop production in a dynamic framework, and (2) the need for a better understanding of the economics of information. To address these issues a stochastic dynamic programming model of a single year's corn production process in east-central Illinois is developed. …
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Implications of the Value of Hydrologic Information to Reservoir Operations -- Learning From the Past
… optimization techniques to build an enhanced stochastic dynamic programming (SDP) model. The enhanced SDP model is applied to the Shelbyville Reservoir, IL, and then compared to two classic SDP formulations. From a data mining procedure, past month's inflow, current month's inflow, past …
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Intertemporal portfolio choice: An application to agricultural investment
… costs. Optimal decisions are derived using a stochastic dynamic programming (SDP) model which incorporates the stochastic dynamic nature of investment returns and the interrelationships between financial structure and investment decisions when the costs of bankruptcy are considered. Results …
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Long term contracts and farm inflexibility premium in the production of cellulosic ethanol
… a farmer when a long term contract is signed. A stochastic dynamic programming model is solved and with the help of Microsoft Excel numerically evaluated to illustrate the marginal inflexibility premium is increasing with contract length and the level of price variability, and is decreasing with …
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Pricing of Swing Options: A Monte Carlo Simulation Approach
… pricing problem is formulated as a stochastic optimal control problem in discrete time and state space. We present a stochastic dynamic programming algorithm which is based on piecewise linear concave approximation of value functions. This algorithm yields the value of the swing …
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Models of intelligence operations
… is modelled as a novel finite horizon Bayesian stochastic dynamic programming problem, namely the multi-armed bandit allocation (MABA) problem. The MABA framework models the efforts of a processor to search for intelligence items of the highest importance by making sequential samples from a …
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Decision tools for electricity transmission service and pricing : a dynamic programming approach
… this thesis, the decision-making is posed as a stochastic dynamic programming problem, and through simulations the strength of this method is demonstrated. This resource allocation problem is first posed as a centrally coordinated dynamic programming problem, computed by one entity at a system- …
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The effects of tax evasion on economic growth: a stochastic growth model approach
… their implications for economic growth through a stochastic growth model in discrete-time. Taxation is important for many aspects for growth. Tax evasion creates negative impacts on the economy such as the fall in gov- ernment revenues, that fund public infrastructure, education and other …
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Discussão de critérios de operação de sistemas hidrelétricos interligados
… generation. This thesis explores simplified stochastic models in order to obtain optimum operation rules for interconnected hydropower systems according to two different criteria. It also presents the consequences of adopting each criterion specially in regard to the flows of energy among …
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The Energy Box : comparing locally automated control strategies of residential electricity consumption under uncertainty
… or time-sequenced, provide better outcomes. Stochastic dynamic programming is the primary optimization engine. The optimization goal is to balance cost minimization with thermal comfort as specified by consumer preferences. The results demonstrate that the desired general energy management …
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Computing the policy parameters for perishable inventory management and cold supply chains under stochastic demand
… supply chains with environmental concerns under stochastic demand, as well as tackling and dealing with the demand uncertainty and fluctuations arising from the nature of demand patterns. The solutions we present in this dissertation for the perishability problem hybridises the well-known …
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Actor-critic algorithms
… and precise objectives, can be formulated as stochastic dynamic programming problems in which the objective of decision making is to maximize a single "overall" reward. In these formulations, finding an optimal decision policy involves computing a certain "value function" which assigns to each …
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Stochastic dynamic optimization of consumption and the induced price elasticity of demand in smart grids
… model of consumer behavior in response to stochastically-varying electricity prices, and a characterization of price-elasticity of demand created by optimal utilization of storage and the flexibility to shift certain demands to periods of lower prices. The approach is based on analytical …
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