The article is dedicated to the field of ant algorithms. It focuses on the problem of searching the shortest path in a graph using ant algorithms in combination with some artificial intelligence methods: evolutionary algorithms and multi-agent systems. The article presents a simulation program, which is able to search the shortest path in a graph. The process of searching the solution is simulated also in a graphical way – in a visual form. Agents, which simulate ants in our work, need only a limited memory. Thus, the use of the presented implementation is not restricted by the complexity of the solved problem. It is an advantage of our simulation. The size of population is controlled by natural selection. On the other hand, agents need more time to get lost in bigger environments. Therefore, the population size increases more quickly in greater environments. The implementation is adaptive as well. If some edge – graph route – is deleted while the program is running or a new one is created, the system is able to adapt to the changed environment. The designed simulation program can be used for solving various problems related to the following domains: electronic market, computer maps, traffic planning, computer games, labyrinth search by a robot, connection-oriented network routing and connection-less network routing.
ant algorithms, evolutionary algorithms, multi agent systems, graph, the shortest path
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