Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Focusing on comprehensive comparisons of the performance of shastic optimization algorithms, this book provides an overview of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective ...