TY - CHAP
T1 - Theoretical advances in evolutionary dynamic optimization
AU - Rohlfshagen, Philipp
AU - Lehre, Per Kristian
AU - Yao, Xin
PY - 2013
Y1 - 2013
N2 - The field of evolutionary dynamic optimization is concerned with the study and application of evolutionary algorithms to dynamic optimization problems: a significant number of new algorithms have been proposed in recent years that are designed specifically to overcome the limitations faced by traditional algorithms in the dynamic domain. Subsequently, a wealth of empirical studies have been published that evaluate the performance of these algorithms on a variety of benchmark problems. However, very few theoretical results have been obtained during this time. This relative lack of theoretical findings makes it difficult to fully assess the strengths and weaknesses of the individual algorithms. In this chapter we provide a review of theoretical advances in evolutionary dynamic optimization. In particular, we argue the importance of theoretical results, highlight the challenges faced by theoreticians and summarise the work that has been done to date. We subsequently identify relevant directions for future research.
AB - The field of evolutionary dynamic optimization is concerned with the study and application of evolutionary algorithms to dynamic optimization problems: a significant number of new algorithms have been proposed in recent years that are designed specifically to overcome the limitations faced by traditional algorithms in the dynamic domain. Subsequently, a wealth of empirical studies have been published that evaluate the performance of these algorithms on a variety of benchmark problems. However, very few theoretical results have been obtained during this time. This relative lack of theoretical findings makes it difficult to fully assess the strengths and weaknesses of the individual algorithms. In this chapter we provide a review of theoretical advances in evolutionary dynamic optimization. In particular, we argue the importance of theoretical results, highlight the challenges faced by theoreticians and summarise the work that has been done to date. We subsequently identify relevant directions for future research.
UR - http://www.scopus.com/inward/record.url?scp=84884221760&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38416-5-9
DO - 10.1007/978-3-642-38416-5-9
M3 - Chapter
AN - SCOPUS:84884221760
SN - 9783642384158
VL - 490
T3 - Studies in Computational Intelligence
SP - 221
EP - 240
BT - Evolutionary Computation for Dynamic Optimization Problems
ER -