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A global-optimization algorithm for mixed-integer nonlinear programs having separable non-convexity

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2009) 5757 LNCS 107-118
DOI: 10.1007/978-3-642-04128-0_10
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Abstract

We present a global optimization algorithm for MINLPs (mixed-integer nonlinear programs) where any non-convexity is manifested as sums of non-convex univariate functions. The algorithm is implemented at the level of a modeling language, and we have had substantial success in our preliminary computational experiments. © 2009 Springer Berlin Heidelberg.

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D’Ambrosio, C., Lee, J., & Wächter, A. (2009). A global-optimization algorithm for mixed-integer nonlinear programs having separable non-convexity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5757 LNCS, pp. 107–118). https://doi.org/10.1007/978-3-642-04128-0_10

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