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Stochastic programming

About: Stochastic programming is a research topic. Over the lifetime, 12343 publications have been published within this topic receiving 421049 citations.


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TL;DR: A "nested fixed point" algorithm is applied that converts the dynamic programming problem into the problem of repeatedly recomputing the fixed point to a contraction mapping operator as a subroutine of a standard nonlinear maximum likelihood program.
Abstract: This paper formulates a model of retirement behavior based on the solution to a stochastic dynamic programming problem. The workers objective is to maximize expected discounted utility over his remaining lifetime. At each time period the worker chooses how much to consume and whether to work full-time, part-time, or exit the labor force. The model accounts for the sequential nature f the retirement decision problem, and the role of expectations of uncertain future variables such as the worker's future lifespan, health status, marital and family status, employment status, as well as earnings from employment, assets, and social security retirement, disability and medicare payments. This paper applies a "nested fixed point" algorithm that converts the dynamic programming problem into the problem of repeatedly recomputing the fixed point to a contraction mapping operator as a subroutine of a standard nonlinear maximum likelihood program. The goal of the paper is to demonstrate that a fairly complex and realistic formulation of the retirement problem can be estimated using this algorithm and a current generation supercomputer, the Cray-2.

163 citations

Journal ArticleDOI
TL;DR: In this paper, a profit-maximizing thermal producer that participates in a sequence of spot markets, namely, day-ahead, automatic generation control (AGC), and balancing markets, is considered.
Abstract: This paper considers a profit-maximizing thermal producer that participates in a sequence of spot markets, namely, day-ahead, automatic generation control (AGC), and balancing markets. The producer behaves as a price-taker in both the day-ahead market and the AGC market but as a potential price-maker in the volatile balancing market. The paper provides a stochastic programming methodology to determine the optimal bidding strategies for the day-ahead market. Uncertainty sources include prices for the day-ahead and AGC markets and balancing market linear price variations with the production of the thermal producer. Results from a realistic case study are reported and analyzed. Conclusions are duly drawn.

163 citations

Journal ArticleDOI
TL;DR: In this article, a stochastic programming formulation for fleet sizing under uncertainty in future demands and operating conditions is presented, where a partial moment measure of risk is incorporated into the expected recourse function.
Abstract: We create a formulation and a solution procedure for fleet sizing under uncertainty in future demands and operating conditions. The formulation focuses on robust optimization, using a partial moment measure of risk. This risk measure is incorporated into the expected recourse function of a two-stage stochastic programming formulation, and stochastic decomposition is used as a solution procedure. A numerical example illustrates the importance of including uncertainty in the fleet sizing problem formulation, and the nature of the fundamental tradeoff between acquiring more vehicles and accepting the risk of potentially high costs if insufficient resources are available.

162 citations

Journal ArticleDOI
TL;DR: In this article, the Shasta-Trinity reservoir operating policies were derived using stochastic dynamic programming (SDP) with different hydrologic state variables, and the authors compared how well SDP models predict their policies and how well these policies performed when simulated.
Abstract: Reservoir operating policies can be derived using stochastic dynamic programming (SDP) with different hydrologic state variables. This paper considers several choices for such hydrologic state variables for SDP models of the Shasta-Trinity system in northern California, for three different benefit functions. We compare how well SDP models predict their policies will perform, as well as how well these policies performed when simulated. For a benefit function stressing energy maximization, all policies did nearly as well, and the choice of the hydrologic state variable mattered very little. For a benefit function with larger water and firm power targets and severe penalties on corresponding shortages, predicted performance significantly overestimated simulated performance, and policies that employed more complete hydrologic information performed significantly better.

162 citations

Journal ArticleDOI
TL;DR: A novel model to decide the joint expansion planning of distributed generation and the distribution network considering the impact of ESS and price-dependent DR programs is presented.
Abstract: The first part of this two-paper series describes the incorporation of demand response (DR) and energy storage systems (ESSs) in the joint distribution and generation expansion planning for isolated systems. The role of DR and ESS has recently attracted an increasing interest in power systems. However, previous models have not been completely adapted in order to treat DR and ESS on an equal footing. The model presented includes DR and ESS in the planning of insular distribution systems. Hence, this paper presents a novel model to decide the joint expansion planning of distributed generation and the distribution network considering the impact of ESS and price-dependent DR programs. The problem is formulated as a stochastic-programming-based model driven by the maximization of the net social benefit. The associated deterministic equivalent is formulated as a mixed-integer linear program suitable for commercially available software. The outcomes of the model are the location and size of new generation and storage units and the distribution assets to be installed, reinforced or replaced. In the second companion paper, an insular case study (La Graciosa, Canary Islands, Spain) is provided illustrating the effects of DR and ESS on social welfare.

162 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023175
2022423
2021526
2020598
2019578
2018532