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EC
2000
96views ECommerce» more  EC 2000»
14 years 9 months ago
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
David A. van Veldhuizen, Gary B. Lamont
GECCO
2010
Springer
189views Optimization» more  GECCO 2010»
14 years 7 months ago
Multiobjective evolutionary algorithm for software project portfolio optimization
Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering ...
Thomas Kremmel, Jirí Kubalík, Stefan...
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
14 years 11 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
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...
CEC
2003
IEEE
15 years 1 months ago
A modified ant colony algorithm for evolutionary design of digital circuits
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. ...
GECCO
2008
Springer
180views Optimization» more  GECCO 2008»
14 years 11 months ago
An agent-based collaborative evolutionary model for multimodal optimization
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...