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GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
13 years 8 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...
TEC
2010
77views more  TEC 2010»
13 years 2 months ago
On Set-Based Multiobjective Optimization
Abstract--Assuming that evolutionary multiobjective optimization (EMO) mainly deals with set problems, one can identify three core questions in this area of research: (i) how to fo...
Eckart Zitzler, Lothar Thiele, Johannes Bader
GECCO
2008
Springer
168views Optimization» more  GECCO 2008»
13 years 8 months ago
Speed-up techniques for solving large-scale bTSP with the Two-Phase Pareto Local Search
We first present a method, called Two-Phase Pareto Local Search, to find a good approximation of the efficient set of the biobjective traveling salesman problem. In the first p...
Thibaut Lust
EC
2011
240views ECommerce» more  EC 2011»
13 years 2 months ago
HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization
Abstract—In the field of evolutionary multi-criterion optimization, the hypervolume indicator is the only single set quality measure that is known to be strictly monotonic with ...
Johannes Bader, Eckart Zitzler
IPPS
2007
IEEE
14 years 2 months ago
Parallel Processing for Multi-objective Optimization in Dynamic Environments
This paper deals with the use of parallel processing for multi-objective optimization in applications in which the objective functions, the restrictions, and hence also the soluti...
Mario Cámara, Julio Ortega, Francisco de To...