DocumentCode
1867680
Title
Biased random key genetic algorithm with hybrid decoding for multi-objective optimization
Author
Tangpattanakul, Panwadee ; Jozefowiez, Nicolas ; Lopez, Pierre
Author_Institution
LAAS, Univ. de Toulouse, Toulouse, France
fYear
2013
fDate
8-11 Sept. 2013
Firstpage
393
Lastpage
400
Abstract
A biased random key genetic algorithm (BRKGA) is an efficient method for solving combinatorial optimization problems. It can be applied to solve both single-objective and multi-objective optimization problems. The BRKGA operates on a chromosome encoded as a key vector of real values between [0, 1]. Generally, the chromosome has to be decoded by using a single decoding method in order to obtain a feasible solution. This paper presents a hybrid decoding, which combines the operation of two single decoding methods. This hybrid decoding gives two feasible solutions from the decoding of one chromosome. Experiments are conducted on realistic instances, which concern acquisition scheduling of agile Earth observing satellites.
Keywords
combinatorial mathematics; genetic algorithms; BRKGA; acquisition scheduling; agile Earth observing satellites; biased random key genetic algorithm; combinatorial optimization problems; hybrid decoding; hybrid decoding method; multiobjective optimization; multiobjective optimization problems; single decoding method; single-objective optimization problems; Biological cells; Decoding; Genetic algorithms; Optimization; Satellites; Sociology; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
Conference_Location
Krako??w
Type
conf
Filename
6644030
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