Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
Abstract— The role of gradient estimation in global optimization is investigated. The concept of a regional gradient is introduced as a tool for analyzing and comparing different...
Ecosystem-related observations from remote sensors on satellites offer huge potential for understanding the location and extent of global land cover change. This paper presents a c...
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
This paper presents and evaluates a parallel Java implementation of the Finite-Difference Time-Domain (FDTD) method, which is a widely used numerical technique in computational el...