Pages that link to "Item:Q263206"

The following pages link to Combining sampling-based and scenario-based nested Benders decomposition methods: application to stochastic dual dynamic programming (Q263206):

Displaying 29 items.

• Spatio-temporal hydro forecasting of multireservoir inflows for hydro-thermal scheduling (Q323521) (← links)
• Computing tight bounds via piecewise linear functions through the example of circle cutting problems (Q328518) (← links)
• Online spatio-temporal matching in stochastic and dynamic domains (Q1648078) (← links)
• Modelling of hydrothermal unit commitment coordination using efficient metaheuristic algorithm: a hybridized approach (Q1659207) (← links)
• Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: an application to the strategic bidding problem (Q1752849) (← links)
• A new separable piecewise linear learning algorithm for the stochastic empty container repositioning problem (Q2007112) (← links)
• A multistage stochastic programming approach for preventive maintenance scheduling of GENCOs with natural gas contract (Q2023991) (← links)
• A time-consistent Benders decomposition method for multistage distributionally robust stochastic optimization with a scenario tree structure (Q2028454) (← links)
• Adaptive partition-based SDDP algorithms for multistage stochastic linear programming with fixed recourse (Q2070338) (← links)
• Data-driven stochastic optimization for distributional ambiguity with integrated confidence region (Q2079685) (← links)
• Non-convex nested Benders decomposition (Q2097672) (← links)
• On pricing-based equilibrium for network expansion planning. A multi-period bilevel approach under uncertainty (Q2189937) (← links)
• On conditional cuts for stochastic dual dynamic programming (Q2195564) (← links)
• Electric power infrastructure planning under uncertainty: stochastic dual dynamic integer programming (SDDiP) and parallelization scheme (Q2218888) (← links)
• A new convergent hybrid learning algorithm for two-stage stochastic programs (Q2286915) (← links)
• Stochastic dual dynamic programming with stagewise-dependent objective uncertainty (Q2294526) (← links)
• On level regularization with normal solutions in decomposition methods for multistage stochastic programming problems (Q2322551) (← links)
• Data-driven mixed-integer linear programming-based optimisation for efficient failure detection in large-scale distributed systems (Q2673583) (← links)
• Piecewise Linear Function Fitting via Mixed-Integer Linear Programming (Q3386779) (← links)
• High-Performance Prototyping of Decomposition Methods in GAMS (Q4995054) (← links)
• Optimal Power Flow in Distribution Networks Under <i>N</i> – 1 Disruptions: A Multistage Stochastic Programming Approach (Q5085985) (← links)
• Efficient Solution Methods for a General <i>r</i>-Interdiction Median Problem with Fortification (Q5086024) (← links)
• Sampling Scenario Set Partition Dual Bounds for Multistage Stochastic Programs (Q5139855) (← links)
• Accelerating techniques on nested decomposition (Q5268932) (← links)
• Two‐stage stochastic minimum <i>s</i> − <i>t</i> cut problems: Formulations, complexity and decomposition algorithms (Q6087397) (← links)
• The policy graph decomposition of multistage stochastic programming problems (Q6092646) (← links)
• Duality and sensitivity analysis of multistage linear stochastic programs (Q6112560) (← links)
• A nested benders decomposition-based algorithm to solve the three-stage stochastic optimisation problem modeling population-based breast cancer screening (Q6168579) (← links)
• Hybrid simplicial-randomized approximate stochastic dynamic programming for multireservoir optimization (Q6538816) (← links)