Optimum route sequence search in SPN based on ant colony algorithm

Based on the ant colony optimization algorithm and expansion of SPN, a memory extended and continuously timed SPN (MESPN), whose transitions could filter and save information and places could filter information, was proposed. When MESPN is running, enough ants (tokens) walk and leave odor in MESPN so that route selections of tokens can be adjusted, in this way it makes lots of ant walk routes approach to transition sequences with less delay. At last a clear ant walk route can be found on the transition sequence with least delay, and the route search problem of complex SPN is solved to a certain extend. The algorithm gives full consideration on the probability characteristics of each transition's real firing time, can determine the probability distribution that each transition's delay time obeys for any type of SPN. The result of simulation shows that the ant walk route is found along the least delay route effectively by tokens, and the shortest route from initial places to every place of MESPN can be gotten.