Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering ...
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
Evolutionary computation presents a new paradigm shift in hardware design and synthesis. According to this paradigm, hardware design is pursued by deriving inspiration from biologi...
Mostafa Abd-El-Barr, Sadiq M. Sait, Bambang A. B. ...
A novel approach to multimodal optimization called Roaming Agent-Based Collaborative Evolutionary Model (RACE) combining several evolutionary techniques with agent-based modeling ...
Rodica Ioana Lung, Camelia Chira, Dumitru Dumitres...