Journal
MATHEMATICAL PROGRAMMING
Volume 196, Issue 1-2, Pages 907-933Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-022-01872-x
Keywords
Bi-objective; Non-convex; Stochastic dual dynamic programming; Stochastic programming
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Funding
- Northwestern University's Center for Optimization & Statistical Learning (OSL)
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We propose an algorithm for solving a class of bi-objective multistage stochastic linear programs and develop a new variant of the stochastic dual dynamic programming algorithm by exploiting the structure of the cost-to-go functions as saddle functions. We apply our algorithm to a hydro-thermal scheduling problem using data from the Brazilian Interconnected Power System and propose a computationally tractable heuristic for bi-objective stochastic convex programs.
We propose an algorithm for solving a class of bi-objective multistage stochastic linear programs. We show that the cost-to-go functions are saddle functions, and we exploit this structure, developing a new variant of the stochastic dual dynamic programming algorithm. Our algorithm is implemented in the open-source stochastic programming solver SDDP.jl. We apply our algorithm to a hydro-thermal scheduling problem using data from the Brazilian Interconnected Power System. We also propose and implement a computationally tractable heuristic for bi-objective stochastic convex programs.
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