Many real-life problems require the solution of optimization problems. If the objective function is not known analytically, traditional methods are not applicable and multi-extremum (global) optimization (GO) methods must be used. Research in GO is aimed at developing new efficient GO algorithms and at practical use of GO in water resources related and other problems.

In recent publications a brief overview of GO methods is given and nine of them are compared in terms of effectiveness (accuracy), efficiency (number of needed function evaluations) and reliability on several problems. Special attention is given to the problems of models calibration. It has been shown that the developed algorithms - adaptive cluster covering (ACCO) show better performance than some of the popular algorithms, for example genetic algorithm. The global optimization tool GLOBE incorporating nine GO algorithms has been built.

Downloads and support of global optimization tool GLOBE (Windows version)

GLOBE screen dump

Download GLOBE for DOS (not supported)

Using GO in models calibration (introduction)

Some publications (most of them are downloadable here):

Solomatine, D.P. The use of global random search methods for models calibration, Proc. XXVIth Congress of the International Association for Hydraulic Research (IAHR), September 1995, vol.1, pp. 224-229, London.

Solomatine D.P. Genetic and other global optimization algorithms - comparison and use in model calibration. Proc. Intern Conf. Hydroinformatics-98, Balkema, Rotterdam, 1998.

Abebe A.J., Solomatine D.P. Application of global optimization to the design of pipe networks. Proc. Intern Conf. Hydroinformatics-98, Balkema, Rotterdam, 1998.

Solomatine, D.P. Two strategies of adaptive cluster covering with descent and their comparison to other algorithms. Journal of Global Optimization, 1999, vol. 14, No. 1, pp. 55-78.

Solomatine D.P., Dibike Y.B, Kukuric N. Automatic Calibration of Groundwater Models: Using Global Optimization Techniques. Hydrological Sciences J. 1999 (accepted for publication).

Solomatine D.P. Random search methods in model calibration and pipe network design. In: Water Industry Systems: Modelling and Optimization Applications, D. Savic, G. Walters (eds.). Research Studies Press Ltd., 1999, pp. 317-332.

Other resources:

Neumaier's Global Optimization page

Hitch-Hiker's Guide to Evolutionary Computation

Simon Streltsov's Research page

DecisionTree for Optimization Software

Some optimization codes in public domain

EvoNet Working Group: SCONDI

Glasgow Genetic Algorithm Demonstrator

Meta-heuristic Research Group at North Carolina State University