17 citations · 44 across the 17 of their papers we have counts for
14 papers · 1 filter
On Non-Elitist Evolutionary Algorithms Optimizing Fitness Functions with a Plateau
Anton V. Eremeev
We consider the expected runtime of non-elitist evolutionary algorithms (EAs), when they are applied to a family of fitness functions with a plateau of second-best fitness in a Ham…
Runtime Analysis of Fitness-Proportionate Selection on Linear Functions
Duc-Cuong Dang, Anton Eremeev, Per Kristian Lehre
This paper extends the runtime analysis of non-elitist evolutionary algorithms (EAs) with fitness-proportionate selection from the simple OneMax function to the linear functions. N…
Modularity in biological evolution and evolutionary computation
Anton Eremeev, Alexander Spirov
One of the main properties of biological systems is modularity, which manifests itself at all levels of their organization, starting with the level of molecular genetics, ending wi…
Genetic Algorithm with Optimal Recombination for the Asymmetric Travelling Salesman Problem
A. V. Eremeev, Yu. V. Kovalenko
We propose a new genetic algorithm with optimal recombination for the asymmetric instances of travelling salesman problem. The algorithm incorporates several new features that cont…
Hitting times of local and global optima in genetic algorithms with very high selection pressure
Anton Eremeev
The paper is devoted to upper bounds on the expected first hitting times of the sets of local or global optima for non-elitist genetic algorithms with very high selection pressure.…
Level-Based Analysis of Genetic Algorithms for Combinatorial Optimization
Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre
The paper is devoted to upper bounds on run-time of Non-Elitist Genetic Algorithms until some target subset of solutions is visited for the first time. In particular, we consider t…