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Fish School Search
Fish School Search (FSS), proposed by Bastos Filho and Lima Neto in 2008 is, in its basic version, an unimodal optimization algorithm inspired on the collective behavior of fish schools. The mechanisms of feeding and coordinated movement were used as inspiration to create the search operators. The core idea is to make the fishes “swim” toward the positive gradient in order to “eat” and “gain weight”. Collectively, the heavier fishes have more influence on the search process as a whole, what makes the barycenter of the fish school moves toward better places in the search space over the iterations. The FSS uses the following principles: # Simple computations in all individuals (i.e. fish) # Various means of storing information (i.e. weights of fish and school barycenter) # Local computations (i.e. swimming is composed of distinct components) # Low communications between neighboring individuals (i.e. fish are to think local but also be socially aware) # Minimum centralized ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ant Colony Optimization Algorithms
In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through Graph (discrete mathematics), graphs. Artificial ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ants is often the predominant paradigm used. Combinations of artificial ants and local search (optimization), local search algorithms have become a method of choice for numerous optimization tasks involving some sort of Graph (discrete mathematics), graph, e.g., vehicle routing problem, vehicle routing and internet routing. As an example, ant colony optimization is a class of optimization (computer science), optimization algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific Computational problem, p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Bee Colony Algorithm
In computer science and operations research, the artificial bee colony algorithm (ABC) is an optimization algorithm based on the intelligent foraging behaviour of honey bee swarm, proposed by Derviş Karaboğa (Erciyes University) in 2005. Algorithm In the ABC model, the colony consists of three groups of bees: employed bees, onlookers and scouts. It is assumed that there is only one artificial employed bee for each food source. In other words, the number of employed bees in the colony is equal to the number of food sources around the hive. Employed bees go to their food source and come back to hive and dance on this area. The employed bee whose food source has been abandoned becomes a scout and starts to search for finding a new food source. Onlookers watch the dances of employed bees and choose food sources depending on dances. The main steps of the algorithm are given below: * Initial food sources are produced for all employed bees * REPEAT ** Each employed bee goes to a fo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
