Experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimisation problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving a design of a scalable test suite of constrained optimisation problems, in which many features could be easily tuned. Then it would be possible to evaluate merits and drawbacks of the available methods as well as test new methods efficiently. We discuss a new test-case generator for constrained parameter optimisation techniques, which deals with deficiencies of generators proposed earlier. This generator TCG-2 is capable of creating various test problems with different characteristics, including the dimensionality of the problem, number of local optima, number of active constraints at the optimum, topology of the feasible search space, etc. Such a test-case generator is very useful for analysing and comparing different constraint-handling techniques and different nonlinear parameter optimisation techniques.
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