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Approximate nonlinear programming algorithms for solving stochastic programs with recourse

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Abstract

This paper summarizes the main results on approximate nonlinear programming algorithms investigated by the author. These algorithms are obtained by combining approximation and nonlinear programming algorithms. They are designed for programs in which the evaluation of the objective functions is very difficult so that only their approximate values can be obtained. Therefore, these algorithms are particularly suitable for stochastic programming problems with recourse.

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Authors and Affiliations

  1. Department of Mathematics, Nanjing University, P.R. China

    Jinde Wang

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  1. Jinde Wang
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Project supported by the National Natural Science Foundation of China.

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Wang, J. Approximate nonlinear programming algorithms for solving stochastic programs with recourse. Ann Oper Res 31, 371–384 (1991). https://doi.org/10.1007/BF02204858

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