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
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;
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
Conference_Location :
Krako??w