dualdynamic
Dualdynamic is a framework for solving sequential decision problems by integrating dual optimization techniques with dynamic programming. It aims to decompose complex multistage decisions into more manageable components while maintaining global feasibility through dual variables.
The approach builds on Lagrangian relaxation: constraints that link stages are dualized, producing a dual objective
During iterations, subproblems at each stage are solved with fixed multipliers, yielding primal policies and local
Convergence typically requires convexity or convexification of subproblems and appropriate sampling in stochastic settings. In practice,
Applications span energy planning, such as hydroelectric reservoir management, water resources, and multistage portfolio optimization; the
Note that dualdynamic may be used as a general term for related hybrids of dual methods and