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» A Multiobjective Frontier Search Algorithm
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CEC
2008
IEEE
14 years 2 months ago
Evolutionary Multi-objective Simulated Annealing with adaptive and competitive search direction
— In this paper, we propose a population-based implementation of simulated annealing to tackle multi-objective optimisation problems, in particular those of combinatorial nature....
Hui Li, Dario Landa Silva
GECCO
2004
Springer
112views Optimization» more  GECCO 2004»
14 years 28 days ago
Some Issues on the Implementation of Local Search in Evolutionary Multiobjective Optimization
This paper discusses the implementation of local search in evolutionary multiobjective optimization (EMO) algorithms for the design of a simple but powerful memetic EMO algorithm. ...
Hisao Ishibuchi, Kaname Narukawa
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 8 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
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
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
14 years 1 months ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne