Automated reformulation of disjunctive constraints in MINLP optimization |
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| Affiliation: | 1. Department of Mechanical Engineering, University of Mohaghegh Ardabili, P.O. Box 179, Ardabil, Iran;2. Department of Mechanical Engineering, College of Engineering, Takestan Branch, Islamic Azad University, Takestan, Iran;1. Aarhus University, Department of Engineering, Inge Lehmanns Gade 10, Aarhus, Denmark;2. Technical University of Denmark, Department of Civil Engineering, Brovej B.118, Kgs. Lyngby, Denmark;3. Brincker & Georgakis, Inge Lehmanns Gade 10, Aarhus, Denmark;1. Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia;1. Departamento de Engenharia Química, Escola de Química, Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 149, CT, Bl. E, Cidade Universitária, 21941-909 Rio de Janeiro, Brazil;2. Centro Universitário SENAI CIMATEC, Av. Orlando Gomes, 1845, 41650-010 Salvador, Bahia, Brazil;1. Institute of Industrial Engineering and Logistics Optimization, Northeastern University, Shenyang 110819, PR China;2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, PR China;3. Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh 15213, PA, United States |
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| Abstract: | In this paper, a general method for handling disjunctive constraints in a MINLP optimization problem is presented. This method automates the reformulation of an, in a abstract modeling language given, optimization problem into a mathematical problem that is solvable with existing optimization tools. This implementation can use common MILP solvers for linear problems and nonlinear methods for quasi-convex optimization problems. It also includes the possibility to use the logics in the system and solve the system logically using subproblems. |
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