DocumentCode :
1390963
Title :
Test-case generator for nonlinear continuous parameter optimization techniques
Author :
Michalewicz, Zbigniew ; Deb, Kalyanmoy ; Schmidt, Martin ; Stidsen, Thomas
Author_Institution :
Dept. of Comput. Sci., North Carolina Univ., Charlotte, NC, USA
Volume :
4
Issue :
3
fYear :
2000
fDate :
9/1/2000 12:00:00 AM
Firstpage :
197
Lastpage :
215
Abstract :
The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving the design of a scalable test suite of constrained optimization problems, in which many features could be tuned easily. It would then be possible to evaluate the merits and drawbacks of the available methods, as well as to test new methods efficiently. In this paper, we propose such a test-case generator for constrained parameter optimization techniques. This generator is capable of creating various test problems with different characteristics including: 1) problems with different relative sizes of the feasible region in the search space; 2) problems with different numbers and types of constraints; 3) problems with convex or nonconvex evaluation functions, possibly with multiple optima; and 4) problems with highly nonconvex constraints consisting of (possibly) disjoint regions. Such a test-case generator is very useful for analyzing and comparing different constraint-handling techniques
Keywords :
evolutionary computation; nonlinear programming; constrained optimization problems; convex evaluation functions; disjoint regions; evolutionary method; highly nonconvex constraints; nonconvex evaluation functions; nonlinear continuous parameter optimization techniques; test-case generator; Character generation; Computer science; Constraint optimization; Cost accounting; Design optimization; Evolutionary computation; Genetic programming; Helium; Optimization methods; Testing;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/4235.873232
Filename :
873232
Link To Document :
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