Topic
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 method is presented for determining the money value of additional information, additional resources, and the expected cost of uncertainty in the stochastic programming model.
Abstract: This paper presents a further development of discrete stochastic programming, viewed within the context of Bayesian decision theory. Some probability models and information structures (with and without additional information) are discussed, followed by an indication of how the stochastic programming matrix may be set up to reflect the various information structures. Some expected utility theories are then reviewed, and their usefulness in allowing the specification of a wide variety of objective functions for the stochastic programming model is illustrated. Lastly, a method is presented for determining the money value of additional information, additional resources, and the expected cost of uncertainty.
124 citations
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TL;DR: In this article, a stochastic planning framework for the battery energy storage system (BESS) in distribution networks with high wind power penetrations was proposed, aiming to maximise wind power utilisation while minimise the investment and operation costs.
Abstract: In recent years, the battery energy storage system (BESS) has been considered as a promising solution for mitigating renewable power generation intermittencies. This study proposes a stochastic planning framework for the BESS in distribution networks with high wind power penetrations, aiming to maximise wind power utilisation while minimise the investment and operation costs. In the proposed framework, the uncertainties in wind power output and system load are modelled by the Monte-Carlo simulation, and a chance-constrained stochastic optimisation model is formulated to optimally determine the location and capacity of BESS while ensuring wind power utilisation level. Then, the Monte-Carlo simulation embedded differential evolution algorithm is used to solve the problem. Simulation studies performed on a 15-bus radial distribution system prove the efficiency of the proposed method.
124 citations
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TL;DR: The challenge of production and inventory management for blood platelets is the requirement to meet highly uncertain demands, which leads to high levels of outdating as PLTs have a limited “shelf life.”
123 citations
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TL;DR: In this article, a multi-objective stochastic optimal planning method for a stand-alone microgrid consisting of diesel generators, wind turbine generators, photovoltaic generation system and lead-acid batteries is presented.
Abstract: To achieve economic and environmental benefit for the stand-alone microgrid consisting of diesel generators, wind turbine generators, photovoltaic generation system and lead-acid batteries, a multi-objective stochastic optimal planning method and a stochastic chance-constrained programming model are presented. In the model, the optimal objective is to simultaneously minimise the total net present cost and carbon dioxide emission in life cycle; the type and capacity of distributed generation units have been selected as the optimal variables; the loss of capacity is adopted as probability index constraint; the coordinated operation strategies between diesel generators and battery, the multi-unit operation constraints of diesel generators and the reserve capacity have been considered in the hard-circle operation strategy. Considering the uncertainties of wind speed, clearness index and load demand, Markov process transition probability matrix is adopted to synthesise those time series data. Optimal planning for an island microgrid system has been carried out by the planning system for microgrid (PSMG), a self-developed optimal planning software based on the multi-objective stochastic optimal planning method for stand-alone microgrid system.
123 citations
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TL;DR: In this paper, a multi-period multi-objective mixed integer linear programming (MILP) is proposed to design and plan a network of reverse logistics under uncertainty for recycling C&D wastes in which the objectives are represented as profit and social impact maximization and environmental effect minimization.
123 citations