Computational Intelligence for Process-optimization Software
- Oteiza, Paola Patricia
- Ardenghi, Juan Ignacio
- Brignole, Nélida Beatriz
DOIAbstract
This work describes a general algorithm for a cooperative hyper-heuristics that enables the optimization of systems of nonlinear algebraic equations with algebraic constraints. The hyper-heuristics comprises the following agents: Genetic Algorithms, Simulated Annealing and Particle Swarm Optimization. Information exchanges take place effectively among them since the immediate incorporation of solution candidates speeds up the search. Algorithmic performance is illustrated with general test models, most of them corresponding to process systems that have currently been employed in PSE. When running in parallel, numerical results demonstrate that the collaborative hybrid structure with embedded intelligent learning contributes to improve resul...
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