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1、蟻群算法外文文獻(xiàn)翻譯 蟻群算法外文文獻(xiàn)翻譯(含:英文原文及中文譯文 含:英文原文及中文譯文) 英文原文 英文原文 The ant colony optimizationOriginAnt colony algorithm (ant colony optimization, ACO), also known as ant algorithm is a probability -based algorithm is used to find
2、 the optimal path in the graph . It in his doctoral thesis proposed by Marco Dorigo in 1992 , inspired by the behavior of the path of the ants found in the process of looking for food . Ant colony algorithm is a simulate
3、d evolutionary algorithm , preliminary studies show that the algorithm has many excellent properties. Optimization design for PID controller parameters , the results of the results of the ant colony algorithm design and
4、genetic algorithm are compared , the numerical simulation the results show that ant colony algorithm is a new kind of simulated evolutionary optimization effectiveness and value.principleEach ant began to search for food
5、 without first telling them where the food was. When a food is found, it will release a pheromone to the environment, attracting other ants, so that more and more ants will find food! Some ants do not always repeat the s
6、ame path as other ants. They the collective, complex behaviors will emerge. This is the law of the interpretation of artificial life and complexity science! So what are these simple rules?1 ScopeThe range observed by ant
7、s is a checkered world. An ant has a parameter that is a speed radius (typically 3). The range it can observe is a 3*3 checkered world, and the distance that can be moved is also in this range. Inside.2, the environmentT
8、he ant's environment is a virtual world. There are obstacles, other ants, and pheromones. There are two kinds of pheromones. One is the food pheromone that is found by the ants who find food. One is to find the nest.
9、 The ants sprinkled the pheromone of the nest. Each ant can only sense the environmental information within its range. The environment makes the pheromone disappear at a certain rate.3, foraging rulesFind out if there is
10、 food in the range that each ant can sense, and if so, go straight. Otherwise, if there are pheromones and if there are more pheromones in the perceivable range, then it will go to places with a large number of pheromone
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