Multiextremal (GLOBAL) Optimization Algorithms for Engineering Applications
In the course of engineering design and modelling, one often has to determine a number of parameters “optimally” . As examples from the field of water resources management , planning and operation of reservoir systems or water quality treatment plants ,calibration of di f f erent descriptive models , hydrologic time-series analysis etc. can be mentioned.As a rule, the optimality criterion is expressed by some specified objective function, while the feasible damain for parameter selection is usually given by a number of constraints.
Unable to display preview. Download preview PDF.
- Archetti, F. (1980) “Analysis of stochastic strategies for the numerical solution of the global optimiz ation problem” , in: Archetti, F. and Cugiani, M. (eds . ) , Numerical Techniques for Stochastic Systems (North Holland, Amsterdam) , pp. 275–295.Google Scholar
- Dixon, L.C.W. and Szegö, G.P. (eds . ) (1975 , 1978) Towards Global Optimization, Vol. 1–2 . (North-Holland, Amsterdam ) .Google Scholar
- Pintér, J. (1983) “A unified approach to globally∞ invergent one-dimensional optimization algorithms”, Technical report IAMI-83.5 , Istituto per le Applicazioni della Matematica e dell’Informatica CNR, Milan.Google Scholar
- Pintér, J. (1984b ) “Globally convergent methods for n-dimensional multiextremal optimiz ation” ,Mathematis che Operations fors chung und Statistik, Series Optimi z ation (to appear) .Google Scholar
- Strongin, R.G. (1978) Numerical methods for multiextremal problems (in Russian) , (Nauka, Moscow) .Google Scholar