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The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original(More)
Swarm-intelligence-based and bio-inspired algorithms form a hot topic in the developments of new algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based on swarm intelligence, biological systems, physical and chemical systems. Therefore, these algorithms can be called swarm-intelligence-based, bio-inspired, physics-and(More)
— In this paper we present self-adaptive differential evolution algorithm jDElsgo on large scale global optimization. The experimental results obtained by our algorithm on benchmark functions provided for the CEC 2010 competition and special session on Large Scale Global Optimization are presented. The experiments were performed on 20 benchmark functions(More)
Memetic computation (MC) has emerged recently as a new paradigm of efficient algorithms for solving the hardest optimization problems. On the other hand, artificial bees colony (ABC) algorithms demonstrate good performances when solving continuous and combinatorial optimization problems. This study tries to use these technologies under the same roof. As a(More)
The Artificial Bee Colony (ABC) is the name of an optimization algorithm that was inspired by the intelligent behavior of a honey bee swarm. It is widely recognized as a quick, reliable, and efficient methods for solving optimization problems. This paper proposes a hybrid ABC (HABC) algorithm for graph 3-coloring, which is a well-known discrete optimization(More)
This paper proposes a hybrid self-adaptive evolutionary algorithm for graph coloring that is hybridized with the following novel elements: heuristic genotype-phenotype mapping, a swap local search heuristic, and a neutral survivor selection operator. This algorithm was compared with the evolutionary algorithm with the SAW method of Eiben et al., the Tabucol(More)
The firefly algorithm is a member of the swarm intelligence family of algorithms, which have recently showed impressive performances in solving optimization problems. The fire-fly algorithm, in particular, is applied for solving continuous and discrete optimization problems. In order to tackle different optimization problems efficiently and fast, many(More)