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A key aspect of the design of evolutionary and swarm intelligence algorithmsis studying their performance. Statistical comparisons are also a crucial partwhich allows for reliable conclusions to be drawn. In the present paper wegather and examine the approaches taken from different perspectives tosummarise the assumptions made by these statistical tests, the conclusionsreached and the steps followed to perform them correctly. In this paper, weconduct a survey on the current trends of the proposals of statistical analysesfor the comparison of algorithms of computational intelligence and include adescription of the statistical background of these tests. We illustrate the useof the most common tests in the context of the Competition on single-objectivereal parameter optimisation of the IEEE Congress on Evolutionary Computation(CEC) 2017 and describe the main advantages and drawbacks of the use of eachkind of test and put forward some recommendations concerning their use.

Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review