Sciweavers

140
Voted
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 7 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
115
Voted
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 7 months ago
Search--based approaches to the component selection and prioritization problem
This poster paper addresses the problem of choosing sets of software components to combine in component
Mark Harman, Alexandros Skaliotis, Kathleen Steinh...
110
Voted
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 7 months ago
Local search for multiobjective function optimization: pareto descent method
Genetic Algorithm (GA) is known as a potent multiobjective optimization method, and the effectiveness of hybridizing it with local search (LS) has recently been reported in the li...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi
125
Voted
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 7 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles