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Multivariate adaptive regression splines (MARS) is a flexible statistical modeling method that has been popular for data mining applications. MARS has also been employed to approxmiate unknown relationships in optimzation for complex systems, including surrogate optimization, dynamic programming, and two-stage stochastic programming. Given the increasing desire to optimize real world systems, this paper presents an approach to globally optimize a MARS model that allows up to two-way interactionarXiv:2006.15707v1 fatcat:ievyoe4evncdhobittblzfgg4q