It is widely assumed and observed in experiments that the use of diversity mechanisms in evolutionary algorithms may have a great impact on its running time. Up to now there is no rigorous analysis pointing out the use of different mechanisms with respect to the runtime behavior. We consider evolutionary algorithms that differ from each other in the way they ensure diversity and point out situations where the right mechanism is crucial for the success of the algorithm. The algorithms considered either diversify the population with respect to the search points or with respect to function values. Investigating simple plateau functions, we show that using the "right" diversity strategy makes the difference between an exponential and a polynomi...
Abstract- It is widely believed that greater initial population diversity leads to improved performa...
Population diversity is essential for avoiding premature convergence in Genetic Algorithms and for ...
Using diversity mechanisms in evolutionary algorithms for multi-objective optimization problems is c...
AbstractIt is widely assumed and observed in experiments that the use of diversity mechanisms in evo...
Evolutionary algorithms (EAs) simulate the natural evolution of species by iteratively applying evol...
Clearing is a niching method inspired by the principle of assigning the available resources among a...
AbstractEvolutionary algorithms (EAs) find numerous applications, and practical knowledge on EAs is ...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Maintaining diversity is important for the performance of evolutionary algorithms. Diversity mechani...
Maintaining diversity is important for the performance of evolutionary algorithms. Diversity-preserv...
AbstractIn recent years a lot of progress has been made in understanding the behavior of evolutionar...
Clearing is a niching method inspired by the principle of assigning the available resources among a ...
Diversity mechanisms are key to the working behaviour of evolutionary multi-objective algorithms. Wi...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Recently Ulrich and Thiele [14] have introduced evolutionary algorithms for the mixed multi-objectiv...
Abstract- It is widely believed that greater initial population diversity leads to improved performa...
Population diversity is essential for avoiding premature convergence in Genetic Algorithms and for ...
Using diversity mechanisms in evolutionary algorithms for multi-objective optimization problems is c...
AbstractIt is widely assumed and observed in experiments that the use of diversity mechanisms in evo...
Evolutionary algorithms (EAs) simulate the natural evolution of species by iteratively applying evol...
Clearing is a niching method inspired by the principle of assigning the available resources among a...
AbstractEvolutionary algorithms (EAs) find numerous applications, and practical knowledge on EAs is ...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Maintaining diversity is important for the performance of evolutionary algorithms. Diversity mechani...
Maintaining diversity is important for the performance of evolutionary algorithms. Diversity-preserv...
AbstractIn recent years a lot of progress has been made in understanding the behavior of evolutionar...
Clearing is a niching method inspired by the principle of assigning the available resources among a ...
Diversity mechanisms are key to the working behaviour of evolutionary multi-objective algorithms. Wi...
Divergence of character is a cornerstone of natural evolution. On the contrary, evolutionary optimiz...
Recently Ulrich and Thiele [14] have introduced evolutionary algorithms for the mixed multi-objectiv...
Abstract- It is widely believed that greater initial population diversity leads to improved performa...
Population diversity is essential for avoiding premature convergence in Genetic Algorithms and for ...
Using diversity mechanisms in evolutionary algorithms for multi-objective optimization problems is c...