Characterization of CEC Single-Objective Optimization Competition Benchmarks and Algorithms
The present study provides an analysis on the characteristics of single-objective optimization benchmark problems as well as the algorithms used to solve them. The target optimization domain involves the CEC competitions, each consisting a set of mathematical functions. Concerning the optimization tasks, the idea is to investigate the dis/-similarities between different competition scenarios and individual benchmarks. For the solvers, the goal is to detect the dis/-similarities between the algorithms applied to the CEC benchmarks. Those analysis missions are carried out by using the features directly and automatically extracted from the performance data, the quality of the solutions achieved by each algorithm on the benchmarks. The feature extraction process is realized through Singular Value Decomposition. Following the analysis on the algorithms, the potential of algorithm selection has been evaluated to see the performance improvement without actually developing a new algorithm, against those 20 algorithms.
