Computational and Exploratory Landscape Analysis of the GKLS Generator

Over the years, various benchmark suites have been proposed, in which different global function properties are represented, such The GKLS generator is one of the most used testbeds for benchmarking as multi-modality, separability, ill-conditioning, and various other global optimization algorithms. In this paper, we conduct both types of global structures. In the evolutionary computation community, a computational analysis and the Exploratory Landscape Analysis the two most utilized benchmark sets are the Black-Box (ELA) of the GKLS generator. We utilize both canonically used and Optimization Benchmarking (BBOB) suite [5] which is now part of newly generated classes of GKLS-generated problems and show the COCO platform [6], and the suites that were presented at the their use in benchmarking three state-of-the-art methods (from evolutionary Congress on Evolutionary Computation (CEC) competitions (which and deterministic communities) in dimensions 5 and 10. started in 2005 and continue to this day) [9]. As was shown in [3], We show that the GKLS generator produces "needle in a haystack" the characteristics of the functions used in these two benchmarks type problems that become extremely difficult to optimize in higher are quite different. The CEC benchmarks are constructed by using dimensions. Furthermore, we conduct the ELA on the GKLS generator similar subfunctions, which possibly gives an advantage to methods and then compare it to the ELA of two other widely used that perform well on these fewer subfunctions. It was also found benchmark sets (BBOB and CEC 2014), and discuss the meaningfulness that the CEC functions share more similarities among themselves of the results.