Abstract. This paper presents ParadisEO-MOEO, a white-box objectoriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms. This paradig...
Abstract Deciding which computer architecture provides the best performance for a certain program is an important problem in hardware design and benchmarking. While previous approa...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
The Distributed Object Group Framework(DOGF) we constructed supports the grouping of distributed objects that are required for distributed application. From the DOGF, we manage dis...
In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...