Optimization with genetic algorithms

D. Hidalgo, O. Castillo, P. MeUn, Type-1 and type-2 fuzzy inference systems as integration methods in modular neural networks for multimodal biometry and its optimization with genetic algorithms. Inf. Sd. 179, 2123-2145 (2009)... 

Figure 6.25 shows the obtained trajectories for the Type-1 FLC optimized with Genetic Algorithms. From the pictures we can observe that in presence of a disturbance 8 > 30, the Type-1 FLC is not able to achieve the tracking control of the mobile robot. 

K. K. Ahn, and H.P.H. Anh, System modeling and identification of the two-link pneumatic artificial muscle (PAM) manipulator optimized with genetic algorithm, Proceedings 2006 lEEE-ICASE Int. Conf, Busan, Korea, (2006), pp. 4744-4749. 

Pigmented film coating formulations have recently been modeled and optimized to enhance opacity and reduce film cracking with neural networks combined with genetic algorithms [46, 47] as well as being studied with neurofuzzy [48]. In the latter study the rules discovered were consistent with known theory. 

Integer programming has been applied by De Vries [3] (a short English-language description can be found in [2]) for the determination of the optimal configuration of equipment in a clinical laboratory and by De Clercq et al. [4] for the selection of optimal probes for GLC. From a data set with retention indices for 68 substances on 25 columns, sets ofp probes (substances) (p= i,2,..., 20) were selected, such that the probes allow to obtain the best characterization of the columns. This type of application would nowadays probably be carried out with genetic algorithms (see Chapter 27). 

This strategy of integrating neural networks with genetic algorithms has been used to search for the optimal composition of a catalyst for the ammoxidation of propane [62]. In that case, no experiments were performed the network was trained with data published earlier by other authors [63]. However, those data were for only 26 catalysts, thus forming a quite small training set. Even more importantly, the predicted performance of the optimal catalyst, expressed by means of acrylonitrile yield, was not experimentally verified. 

The developed optimization is solved with genetic algorithm as the previous study based on deterministic optimization techniques showed that it is often trapped in local optima, due to highly non-linear nature of formulations in the model. The simulation model and genetic algorithm is interacted to produce high quality optimal solution(s), although computational time is relatively expensive. 

In another work, Poteau and Pastor used a phenomenological tight-binding model together with genetic algorithms in optimizing the structures of small metal clusters with one electron per atom.79... 

Kang, H., Choi, H. and Park, H. (2007) Prediction of molecular solvation ftee energy based on the optimization of atomic solvation parameters with genetic algorithm. /. Chem. Inf. Model., 47, 509-514. 

Once the optimization algorithm is developed, it will be applied to a set of benchmark functions the obtained results will be compared with the results obtained with genetic algorithms and other optimization paradigms. 

T. Eisenhammer, M. Lazarov, M. Leutbecher, U. Schoffel, R. Sizmann, Optimization of interference filters with genetic algorithms applied to silver-based heat minors. Appl. Opt. 32 (31), 6310-6315 (1993)... 

Polifke, W., Geng, W., Dobbeling, K. Optimization of rate coefficients for simplified reaction mechanisms with genetic algorithms. Combust. Flame 113, 119-135 (1998)... 

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