Comparison of nature-inspired population-based algorithms on continuous optimisation problems

Eleven swarm-intelligence-based (SI) and bio-inspired (BI) algorithms are compared with four advanced adaptive differential evolution (DE) variants, the classic DE and the blind random search on two benchmark sets. One of the benchmark sets is the CEC 2011 collection of 22 real-world optimisation problems, the latter is the suite of 30 artificial optimisation problems defined for the competition of the algorithms within CEC 2014. The results of the experiments demonstrate the superiority of the adaptive DE variants both on realworld problems and the artificial CEC 2014 test suite at all the levels of dimension (10, 30, and 50). Some of the SI and BI algorithms perform even worse than the blind random search. The efficiency of the classic DE is comparable with the better performing SI and BI methods. The results entitle to form a recommendation for practitioners: Do not propose a pseudo-new algorithm but select from the optimisation algorithms supported by thorough research and good ranking at international competitions of optimisation algorithms.