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CEC
2007
IEEE
15 years 4 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
81
Voted
EMO
2005
Springer
110views Optimization» more  EMO 2005»
15 years 3 months ago
Parallelization of Multi-objective Evolutionary Algorithms Using Clustering Algorithms
Abstract. While Single-Objective Evolutionary Algorithms (EAs) parallelization schemes are both well established and easy to implement, this is not the case for Multi-Objective Evo...
Felix Streichert, Holger Ulmer, Andreas Zell
70
Voted
EMO
2009
Springer
155views Optimization» more  EMO 2009»
15 years 4 months ago
A Hybrid Integrated Multi-Objective Optimization Procedure for Estimating Nadir Point
A nadir point is constructed by the worst objective values of the solutions of the entire Pareto-optimal set. Along with the ideal point, the nadir point provides the range of obje...
Kalyanmoy Deb, Kaisa Miettinen, Deepak Sharma
EMO
2009
Springer
140views Optimization» more  EMO 2009»
15 years 2 months ago
On Using Populations of Sets in Multiobjective Optimization
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
Johannes Bader, Dimo Brockhoff, Samuel Welten, Eck...
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 3 months ago
Incorporating fuzzy knowledge into fitness: multiobjective evolutionary 3D design of process plants
Designing technical plants is a complex and demanding process. It has been shown that the optimization of the simple facility placement problem is already NP-hard. Optimization of...
Ingo Mierswa