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DOE OSTI · 1755950

Solving Stochastic Dynamic Programming Problems: A Mixed Complementarity Approach

Chang, Wonjun·Ferris, Michael C.·Kim, Youngdae·Rutherford, Thomas F.
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Abstract

We detail a mixed complementarity problem (MCP) formulation of continuous state dynamic programming problems (DP-MCP). We write the solution to projection methods in value function iteration (VFI) as a joint set of optimality conditions that characterize maximization of the Bellman equation; and approximation of the value function. The MCP approach replaces the iterative component of projection based VFI with a one-shot solution to a square system of complementary conditions. We provide three numerical examples to illustrate our approach.

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97 MATHEMATICS AND COMPUTINGComplementarityComputable general equilibriumComputational methodsDynamic Programming

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Chang, Wonjun, Ferris, Michael C., Kim, Youngdae, Rutherford, Thomas F.. 2019-10-04. Solving Stochastic Dynamic Programming Problems: A Mixed Complementarity Approach. https://doi.org/10.1007/s10614-019-09921-y

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