Eftimov T., Korošec P. Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

New York: Springer, 2022. — 141 p.This book explains what is required to make a more robust statistical comparison of the performance achieved by meta-heuristics. It does not explain how to develop a new single- or multi-objective meta-heuristic, or how to run it on a specific or a set of problem instances and collect the experimental data. It deals in which statistical analysis should be made once the experimental data is collected to obtain robust statistical outcomes.Meta-heuristic Stochastic Optimization.
Benchmarking Theory.
Introduction to Statistical Analysis.
Approaches to Statistical Comparisons Used for Stochastic Optimization Algorithms.
Deep Statistical Comparison in Multi-Objective Optimization.
Deep Statistical Comparison in Single-Objective Optimization.
DSCTool — A Web-Service-Based e-Learning Tool.