Computational strategies for improved MINLP algorithms

• Published in: Computers & chemical engineering Vol. 75; pp. 40 - 48
• Main Authors: Su, Lijie, Tang, Lixin, Grossmann, Ignacio E.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 06-04-2015
• Subjects: Algorithms; Approximation; Chemical engineering; Computation; Convergence; Cutting Plane; Generalized Benders Decomposition (GBD); Mathematical analysis; Mathematical models; Mixed Integer Nonlinear Programming (MINLP); Outer Approximation (OA); Strategy; Cutting Plane; Generalized Benders Decomposition (GBD); Mixed Integer Nonlinear Programming (MINLP); Outer Approximation (OA)
• ISSN: 0098-1354; 1873-4375
• DOI: 10.1016/j.compchemeng.2015.01.015

•Three new computational strategies are presented for the OA and GBD methods.•The properties and convergence of the proposed strategies are analyzed.•Five new MINLP algorithms are developed based on the proposed strategies.•Results of numerical experiments are reported for benchmark MINLP problems.
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.