We investigate the biologically motivated selfreproduction strategies, by numerical and analytical calculations. In the analytical part we show that each of these strategies can be reduced to a eigenvalue problem of Sturm-Liouville-type. The properties of the landscape and the dynamics of the optimization are encoded in the spectrum of the Hamiltonian, which is different in both cases. We discuss some model cases with exact solutions and compare it with simulations
This book presents powerful techniques for solving global optimization problems on manifolds by mean...
. In this paper we describe evolutionary heuristics for numerically solving systems of several, inte...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computa...
. We investigate the biologically motivated selfreproduction strategies, by numerical and analytical...
Evolutionary Algorithms have proved to be a powerful tool for solving complex optimization problems....
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
ABSTRACT By the advances in the Evolution Algorithms (EAs) and the intelligent optimization methods...
In this paper, we present an overview of the most important representatives of algorithms gleaned fr...
The objective of Evolutionary Computation is to solve practical problems (e.g.optimization, data min...
Abstract. Evolution strategies are inspired in biology and form part of a larger research field know...
Abbreviated Abstract: The objective of Evolutionary Computation is to solve practical problems (e.g....
Abstract: This paper further introduces continuous optimization into the fields of computational bio...
Many real-world optimization problems occur in environments that change dynamically or involve stoch...
International audienceEvolution strategies are evolutionary algorithms that date back to the 1960s a...
In this thesis a general mathematical framework to describe evolutionary algorithms is developed. Th...
This book presents powerful techniques for solving global optimization problems on manifolds by mean...
. In this paper we describe evolutionary heuristics for numerically solving systems of several, inte...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computa...
. We investigate the biologically motivated selfreproduction strategies, by numerical and analytical...
Evolutionary Algorithms have proved to be a powerful tool for solving complex optimization problems....
Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are ...
ABSTRACT By the advances in the Evolution Algorithms (EAs) and the intelligent optimization methods...
In this paper, we present an overview of the most important representatives of algorithms gleaned fr...
The objective of Evolutionary Computation is to solve practical problems (e.g.optimization, data min...
Abstract. Evolution strategies are inspired in biology and form part of a larger research field know...
Abbreviated Abstract: The objective of Evolutionary Computation is to solve practical problems (e.g....
Abstract: This paper further introduces continuous optimization into the fields of computational bio...
Many real-world optimization problems occur in environments that change dynamically or involve stoch...
International audienceEvolution strategies are evolutionary algorithms that date back to the 1960s a...
In this thesis a general mathematical framework to describe evolutionary algorithms is developed. Th...
This book presents powerful techniques for solving global optimization problems on manifolds by mean...
. In this paper we describe evolutionary heuristics for numerically solving systems of several, inte...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computa...