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. I
[[abstract]]Genetic algorithm is a novel optimization technique for solving constrained optimization...
This paper presents a biased random-key genetic algorithm for k-medoids clustering problem. A novel ...
In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partit...
International audienceA biased random key genetic algorithm (BRKGA) is an efficient method for solvi...
A random-key genetic algorithm is an evolutionary metaheuristic for discrete and global optimization...
Random key genetic algorithms are heuristic methods for solving combinatorial optimization problems....
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
Abstract: In this paper, we study extensions of Genetic Algorithm (GA) to incorporate improved sampl...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
In genetic algorithms (GAs), is it better to use binary encoding schemes or floating point encoding ...
Genetic algorithms are group optimisation techniques which can handle multiple objective functions s...
Global optimization seeks a minimum or maximum of a multimodal function over a discrete orcontinuous...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
This work presents a biased random-key genetic algorithm (BRKGA) to solve the electric distribution ...
Successful engineering design generally requires the resolution of various conflicting design objecti...
[[abstract]]Genetic algorithm is a novel optimization technique for solving constrained optimization...
This paper presents a biased random-key genetic algorithm for k-medoids clustering problem. A novel ...
In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partit...
International audienceA biased random key genetic algorithm (BRKGA) is an efficient method for solvi...
A random-key genetic algorithm is an evolutionary metaheuristic for discrete and global optimization...
Random key genetic algorithms are heuristic methods for solving combinatorial optimization problems....
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
Abstract: In this paper, we study extensions of Genetic Algorithm (GA) to incorporate improved sampl...
In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (...
In genetic algorithms (GAs), is it better to use binary encoding schemes or floating point encoding ...
Genetic algorithms are group optimisation techniques which can handle multiple objective functions s...
Global optimization seeks a minimum or maximum of a multimodal function over a discrete orcontinuous...
Genetic algorithm (GA) is a well-known population-based optimization algorithm. GA utilizes a random...
This work presents a biased random-key genetic algorithm (BRKGA) to solve the electric distribution ...
Successful engineering design generally requires the resolution of various conflicting design objecti...
[[abstract]]Genetic algorithm is a novel optimization technique for solving constrained optimization...
This paper presents a biased random-key genetic algorithm for k-medoids clustering problem. A novel ...
In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partit...