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.
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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: Fiat, A., Sanders, P. (eds) Algorithms - ESA 2009. ESA 2009. Lecture Notes in Computer Science, vol 5757. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04128-0_10
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DOI: https://doi.org/10.1007/978-3-642-04128-0_10
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