Abstract. While Single-Objective Evolutionary Algorithms (EAs) parallelization schemes are both well established and easy to implement, this is not the case for Multi-Objective Evo...
Evolutionary algorithms (EAs) produce a vast amount of data by recurring processes, e.g., selection, recombination, or mutation, that work on populations of solutions for a speciï...
Abstract- In this paper, we apply an Evolutionary Algorithm (EA) to solve the Rubinstein’s Basic AlternatingOffer Bargaining Problem, and compare our experimental results with it...
The task of automatic design space exploration of heterogeneous multi-processor systems is often tackled with Evolutionary Algorithms. In this paper, we propose a novel approach i...
Thomas Schlichter, Christian Haubelt, Frank Hannig...
Abstract. Memetic Algorithms are the most frequently used hybrid of Evolutionary Algorithms (EA) for real-world applications. This paper will deal with one of the most important ob...
Abstract. In this paper, a general framework of quantum-inspired multiobjective evolutionary algorithms is proposed based on the basic principles of quantum computing and general s...
A new model for automatic generation of Evolutionary Algorithms (EAs) by evolutionary means is proposed in this paper. The model is based on a simple Genetic Algorithm (GA). Every...
There has been a considerable body of work on search–based test data generation for branch coverage. However, hitherto, there has been no work on multi–objective branch covera...
We analyze the performance of evolutionary algorithms on various matroid optimization problems that encompass a vast number of efficiently solvable as well as NP-hard combinatoria...
In this paper, we describe Automated Red Teaming (ART), a concept that uses Evolutionary Algorithm (EA), Parallel Computing and Simulation to complement the manual Red Teaming eff...
Chwee Seng Choo, Ching Lian Chua, Su-Han Victor Ta...