Using redundancy to strengthen the relaxation for the global optimization of MINLP problems

作者：Ruiz Juan P; Grossmann Ignacio E^*

来源：Computers & Chemical Engineering, 2011, 35(12): 2729-2740.

DOI：10.1016/j.compchemeng.2011.01.035

• Global optimization
• Reduction constraints
• Tight formulations

In this paper we present a strategy to improve the relaxation for the global optimization of non-convex MINLPs. The main idea consists in recognizing that each constraint or set of constraints has a meaning that comes from the physical interpretation of the problem. When these constraints are relaxed part of this meaning is lost. Adding redundant constraints that recover that physical meaning strengthens the relaxation. We propose a methodology to find such redundant constraints based on engineering knowledge and physical insight.

• 出版日期2011-12-14