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EMO
2001
Springer
107views Optimization» more  EMO 2001»
13 years 12 months ago
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Joshua D. Knowles, Richard A. Watson, David Corne
JUCS
2008
150views more  JUCS 2008»
13 years 7 months ago
Optimal Sensor Network Layout Using Multi-Objective Metaheuristics
: Wireless Sensor Networks (WSN) allow, thanks to the use of small wireless devices known as sensor nodes, the monitorization of wide and remote areas with precision and liveness u...
Guillermo Molina, Enrique Alba, El-Ghazali Talbi
GECCO
2006
Springer
135views Optimization» more  GECCO 2006»
13 years 11 months ago
Single and multi-objective genetic operators in object-oriented conceptual software design
This poster paper investigates the potential of single and multiobjective genetic operators with an object-oriented conceptual design space. Using cohesion as an objective fitness...
Christopher L. Simons, Ian C. Parmee
CEC
2008
IEEE
14 years 1 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
13 years 11 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