These two volumes, LNCS 7076 and LNCS 7077, constitute the refereed proceedings of the Second International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, held in Visakhapatnam, India, in December 2011. The 124 revised full papers presented in both volume…
These two volumes, LNCS 7076 and LNCS 7077, constitute the refereed proceedings of the Second International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2011, held in Visakhapatnam, India, in December 2011. The 124 revised full papers presented in both volume…
Evolutionary computation, machine learning and data mining in bioinformatics: 9th European conference, EvoBIO 2011, Torino, Ita…
by Pizzuti, Clara, EvoBIO (Conference), Turin, Italy), Ritchie, Marylyn DeRiggi, Giacobini, Mario
fromLNCS sublibrary. SL 1, Theoretical computer science and gen…
Evolutionary computation, machine learning and data mining in bioinformatics: 9th European conference, EvoBIO 2011, Torino, Ita…
by Pizzuti, Clara, EvoBIO (Conference), Turin, Italy), Ritchie, Marylyn DeRiggi, Giacobini, Mario
fromLNCS sublibrary. SL 1, Theoretical computer science and gen…
This book constitutes the refereed proceedings of the 9th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 events. The 12 revised full papers prese…
"This book explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. It provides scholars, academics, and practitioners with a fundamental, comprehensive collection…
Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large num…
Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large num…
"This book explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. It provides scholars, academics, and practitioners with a fundamental, comprehensive collection…
"This book explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. It provides scholars, academics, and practitioners with a fundamental, comprehensive collection…
Evolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for str…
ʺEvolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for st…
Contemporary evolution strategies
by Bäck, Thomas, Krause, Peter, Foussette, Christophe
Evolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for str…