Computational strategies for improved MINLP algorithms

In order to improve the efficiency for solving MINLP problems, we present in this paper three computational strategies. These include multiple-generation cuts, hybrid methods and partial surrogate cuts for the Outer Approximation and Generalized Benders Decomposition. The properties and convergence of the strategies are analyzed. Based on the proposed strategies, five new MINLP algorithms are developed, and their implementation is discussed. Results of numerical experiments for benchmark MINLP problems are reported to demonstrate the efficiency of the proposed methods.