Abstract
We present an interval global optimization algorithm using a modified monotonicity test. The improvement applies to constrained problems and can result in significant speedup, when constraints are sparse, i.e. they “bind” a few of the variables, not all of them. A theorem that ensures the correctness of the new tool, is given and proved. The improved method is applied to an economic problem of setting optimal prices on a couple of products.
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Kubica, B.J., Niewiadomska-Szynkiewicz, E. (2007). An Improved Interval Global Optimization Method and Its Application to Price Management Problem. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_123
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DOI: https://doi.org/10.1007/978-3-540-75755-9_123
Publisher Name: Springer, Berlin, Heidelberg
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