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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Papers
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19 Jun 2012
TL;DR: Uncertainty in Optimization, Modeling Feasibility and Dynamics, and Stochastic Discount Factors.
Abstract: Uncertainty in Optimization.-Modeling Feasibility and Dynamics.-Modeling the Objective Function.- Scenario tree generation, With Michal Kaut.-Service network design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic.- A multi-dimensional newsboy problem with substitution, With Hajnalka Vaagen.- Stochastic Discount Factors.- Long Lead Time Production, With Aliza Heching.- References.- Index"/p>
201 citations
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TL;DR: A Monte-Carlo simulation-based algorithm is described that integrates a sample average approximation scheme with a Benders decomposition algorithm to solve problems having stochastic independent transportation costs.
201 citations
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TL;DR: This paper presents the theoretical developments of a novel approach for the optimization of design models involving stochastic parameters involving decomposition based approach to deal with linear and convex nonlinear models involving uncertainty described by arbitrary probability distribution functions.
201 citations
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TL;DR: This work forms a Markov decision process model of the stochastic inventory routing problem and proposes approximation methods to find good solutions with reasonable computational effort and indicates how the proposed approach can be used for other Markov decisions involving the control of multiple resources.
Abstract: This work is motivated by the need to solve the inventory routing problem when implementing a business practice called vendor managed inventory replenishment (VMI). With VMI, vendors monitor their customers' inventories and decide when and how much inventory should be replenished at each customer. The inventory routing problem attempts to coordinate inventory replenishment and transportation in such a way that the cost is minimized over the long run. We formulate a Markov decision process model of the stochastic inventory routing problem and propose approximation methods to find good solutions with reasonable computational effort. We indicate how the proposed approach can be used for other Markov decision processes involving the control of multiple resources.
200 citations
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TL;DR: In this paper, a short-term production plan for a price-taking hydropower plant operating under uncertainty is developed within the framework of multi-stage mixed-integer linear stochastic programming.
199 citations