2 resultados para Cival penalties
em Duke University
Resumo:
A set of 13 US based experts in post-combustion and oxy-fuel combustion CO2 capture systems responded to an extensive questionnaire asking their views on the present status and future expected performance and costs for amine-based, chilled ammonia, and oxy-combustion retrofits of coal-fired power plants. This paper presents the experts' responses for technology maturity, ideal plant characteristics for early adopters, and the extent to which R&D and deployment incentives will impact costs. It also presents the best estimates and 95% confidence limits of the energy penalties associated with amine-based systems. The results show a general consensus that amine-based systems are closer to commercial application, but potential for improving performance and lowering costs is limited; chilled ammonia and oxy-combustion offer greater potential for cost reductions, but not without greater uncertainty regarding scale and technical feasibility. © 2011 Elsevier Ltd.
Resumo:
We describe a general technique for determining upper bounds on maximal values (or lower bounds on minimal costs) in stochastic dynamic programs. In this approach, we relax the nonanticipativity constraints that require decisions to depend only on the information available at the time a decision is made and impose a "penalty" that punishes violations of nonanticipativity. In applications, the hope is that this relaxed version of the problem will be simpler to solve than the original dynamic program. The upper bounds provided by this dual approach complement lower bounds on values that may be found by simulating with heuristic policies. We describe the theory underlying this dual approach and establish weak duality, strong duality, and complementary slackness results that are analogous to the duality results of linear programming. We also study properties of good penalties. Finally, we demonstrate the use of this dual approach in an adaptive inventory control problem with an unknown and changing demand distribution and in valuing options with stochastic volatilities and interest rates. These are complex problems of significant practical interest that are quite difficult to solve to optimality. In these examples, our dual approach requires relatively little additional computation and leads to tight bounds on the optimal values. © 2010 INFORMS.