1. Integrated Differential Evolution for Global Optimization and Its Performance for Modeling Vapor–Liquid Equilibrium Data
- Author
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Adrian Bonilla-Petriciolet, Haibo Zhang, and Gade Pandu Rangaiah
- Subjects
Mathematical optimization ,Computer science ,Estimation theory ,General Chemical Engineering ,Thermodynamics ,General Chemistry ,Function (mathematics) ,Industrial and Manufacturing Engineering ,Term (time) ,Nonlinear system ,Differential evolution ,Mutation (genetic algorithm) ,Vapor–liquid equilibrium ,Global optimization - Abstract
Parameter estimation in thermodynamic models has been of great interest in chemical engineering because of its complex nature, including nonlinearity, flat objective function in the neighborhood of the global optimum, badly scaled model, and nondifferential term(s) in the equations. In this article, a stochastic global optimization algorithm called integrated differential evolution (IDE) is introduced to solve the parameter estimation problems for modeling vapor–liquid equilibrium (VLE) data. In IDE, the choice of mutation strategy and associated parameters are adapted according to the learning experience from previous generations. The tabu list used in IDE can avoid revisiting the same area and avoid unnecessary function evaluations. A novel and effective stopping criterion based on the number of rejected points during the generation of a trial vector is tested and compared with other criteria. Furthermore, IDE uses a local optimizer after the global search to find the optimum accurately and efficiently....
- Published
- 2011