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Exploration and exploitation are two strategies used to search the problem space in Evolutionary Algorithms (EAs). To significantly increase the performance of these optimization techniques in terms of the solution optimality is to strike the right balance between exploration and exploitation. Firefly is one of the most favored EAs. In this study, we introduce an entire fuzzy system to tune dynamically...
Krill Herd optimization algorithm which is a new metaheuristic search algorithm mimics the herding behavior of krill individuals. The significant characteristic of meta-heuristic algorithms is their ability in combination of local search and global search. This property can adjust the contribution of local search and global search in initial step and during searching process and plays crucial role...
The Standard Krill Herd(SKH) optimization algorithm is one of the meta-heuristic algorithms which is proposed based on herding behavior of krill individuals in the nature for solving optimization problems. Considering that SKH is a meta-heuristic algorithm, two main properties of this algorithm is using mixture of random search or exploration and local search or exploitation. Keeping the exploration...
Firefly algorithm is one of the metaheuristic algorithms which are used to solve optimization problems. Firefly algorithm is such a population-based algorithm so that their group behavior and interaction result in a swarm Intelligence that is used to find the best and fittest firefly. Since this algorithm is based on the search agents, it utilizes different agents with different qualities in searching...
Firefly algorithm is one of the metaheuristic algorithms which are used for solving optimization problems. This algorithm is a population-based algorithm like most of algorithms in this class that utilizes swarm intelligence to search the problem space. Searching steps in this algorithm include random step or random search and information - based step or local search. So, these two types of movement,...
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