Abstract
Optimization problems often arise in the context of scientific-engineering research and practice. In many situations that require optimization, there is no need to develop new, highly customized software for a new problem, because there are readily usable optimization packages to choose from. Benchmarking and testing software environments can greatly assist the process of choosing an appropriate optimization tools. The benchmarking environments typically include a substantial collection of well-known and widely used test functions; they also offer a properly defined methodology to compare the solvers considered. One of these benchmarking environments is called COCO (an abbreviation that stands for COmparing Continuous Optimizers). COCO has been used at the annual BBOB (Black-Box Optimization Benchmarking) workshops. COCO assesses the capabilities of optimization solvers based on a given collection of test problems and evaluation criteria, under identical and fully reproducible circumstances. The goal of our present study is to benchmark the LGO (Lipschitz Global Optimizer) solver suite and to compare it to several other solvers using COCO.
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