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CEC
2007
IEEE
13 years 11 months ago
Improving hypervolume-based multiobjective evolutionary algorithms by using objective reduction methods
— Hypervolume based multiobjective evolutionary algorithms (MOEA) nowadays seem to be the first choice when handling multiobjective optimization problems with many, i.e., at lea...
Dimo Brockhoff, Eckart Zitzler
EC
2011
240views ECommerce» more  EC 2011»
12 years 12 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
EMO
2006
Springer
182views Optimization» more  EMO 2006»
13 years 8 months ago
Multi-objective Pole Placement with Evolutionary Algorithms
Multi-Objective Evolutionary Algorithms (MOEA) have been succesfully applied to solve control problems. However, many improvements are still to be accomplished. In this paper a new...
Gustavo Sánchez, Minaya Villasana, Miguel S...
COR
2011
12 years 12 months ago
An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
The Vehicle Routing Problem with Time Windows is a complex combinatorial problem with many real-world applications in transportation and distribution logistics. Its main objective...
Abel Garcia-Najera, John A. Bullinaria
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 8 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace