Interpolated continuous optimisation problems with tunable landscape features

In this paper, we introduce a new class of optimisation problems with tunable landscape features called Interpolated Continuous Optimisation Problems (ICOPs). ICOPs are defined by a search space, a set of solutions called seeds at selected positions, and their fitnesses. The rest of the fitness landscape is interpolated from the seeds using the inverse distance weighting interpolation function. We show that by evolving the position and the fitness of the seeds, we can generate extreme problems with respect to different fitness landscape measures.

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