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2016•Macroeconomic DynamicsOpen access

A NONLINEAR PROGRAMMING METHOD FOR DYNAMIC PROGRAMMING

Yongyang Cai, Kenneth L. Judd, Thomas S. Lontzek, Valentina Michelangeli, Che-Lin Su

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Abstract

A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

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What this paper is about

A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

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Available abstract

A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

Key concepts: Discretization, Nonlinear programming, Dynamic programming, Nonlinear system, Mathematical optimization, Computer science, Reactive programming, Fractional programming

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