TY  - CHAP
AU  - Maxim A. Dulebenets
ED  - Javier Del Ser
ED  - Eneko Osaba
Y1  - 2018-07-18
PY  - 2018
T1  - Evaluation of Non-Parametric Selection Mechanisms in Evolutionary Computation: A Case Study for the Machine Scheduling Problem
N2  - Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.
BT  - Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization
SP  - Ch. 3
UR  - https://doi.org/10.5772/intechopen.75984
DO  - 10.5772/intechopen.75984
SN  - 978-1-78923-329-2
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-05-11
ER  -