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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.


Papers
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Journal ArticleDOI
TL;DR: In this article, a three-stage mixed-integer stochastic programming model for disaster response planning is presented, considering the opening of local distribution facilities, initial allocation of supplies, and last mile distribution of aid.
Abstract: This paper presents a three-stage mixed-integer stochastic programming model for disaster response planning, considering the opening of local distribution facilities, initial allocation of supplies, and last mile distribution of aid. The vehicles available for transportation, the state of the infrastructure and the demand of the potential beneficiaries are considered as stochastic elements. Extensive computational testing performed on realistic instances shows that the solutions produced by the stochastic programming model are significantly better than those produced by a deterministic expected value approach.

168 citations

Journal ArticleDOI
TL;DR: A modified and computationally efficient progressive hedging algorithm with scenario bundling is introduced for resilience-oriented design to protect distribution grids against high-impact but low-probability extreme weather events.
Abstract: This paper proposes a resilience-oriented design (ROD) technique to protect distribution grids against high-impact but low-probability extreme weather events. The problem is formulated as a two-stage stochastic mixed integer problem. The first stage is to make ROD decisions, i.e., hardening existing distribution lines and deploying ROD resources such as back-up distributed generators and automatic switches. The second stage evaluates the system operation cost during a realized extreme weather event and repair cost after the event. A novel modeling strategy is proposed to deal with the decision-dependent uncertainty of distribution line damage status, which is affected by the first-stage hardening decisions. As both stages have binary variables, a modified and computationally efficient progressive hedging algorithm with scenario bundling is introduced. The algorithm performance is evaluated by calculating lower bounds of solutions. The proposed model and algorithms are demonstrated on 34-bus and 123-bus test feeders.

168 citations

Journal ArticleDOI
01 Jan 2007
TL;DR: Experimental results show that the proposed stochastic beam search is more accurate and efficient than both the state-of-the-art meta-heuristic and the traditional determinist beam search.
Abstract: In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new multiple stage search method, namely stochastic beam search algorithm, is proposed to solve it. New techniques such as an improved beam search scheme, a two-phase node goodness estimation, and a stochastic node selection criteria are proposed. Real-life information provided by Singapore Port was collected as our test data. Experimental results show that the proposed stochastic beam search is more accurate and efficient than both the state-of-the-art meta-heuristic and the traditional determinist beam search.

167 citations

Journal ArticleDOI
TL;DR: This paper proposes a method for optimizing convex performance functions in stochastic systems, which can include expected performance in static systems and steady-state performance in discrete-event dynamic systems; they may be nonsmooth.
Abstract: In this paper we propose a method for optimizing convex performance functions in stochastic systems. These functions can include expected performance in static systems and steady-state performance in discrete-event dynamic systems; they may be nonsmooth. The method is closely related to retrospective simulation optimization; it appears to overcome some limitations of stochastic approximation, which is often applied to such problems. We explain the method and give computational results for two classes of problems: tandem production lines with up to 50 machines, and stochastic PERT (Program Evaluation and Review Technique) problems with up to 70 nodes and 110 arcs.

167 citations

Journal ArticleDOI
TL;DR: This paper takes a basic version of the problem in which periodic schedules are built for a number of vehicles and where only the demand may vary stochastically, and investigates the importance of introducing stochastic elements into service network design formulations.
Abstract: The objective of this paper is to investigate the importance of introducing stochastic elements into service network design formulations. To offer insights into this issue, we take a basic version of the problem in which periodic schedules are built for a number of vehicles and where only the demand may vary stochastically. We study how solutions based on uncertain demand differ from solutions based on deterministic demand and provide qualitative descriptions of the structural differences. Some of these structural differences provide a hedge against uncertainty by using consolidation. This way we get consolidation as output from the model rather than as an a priori required property. Service networks with such properties are robust, as seen by the customers, by providing operational flexibility.

167 citations


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