Tourist path finding using Artificial Bee Colony algorithm

Tourism is one of human activities that have strong cultural، social and economic effects on societies. One of the concerns of the tourist is how to select the order and the path to the tourism centers he/she wants to visit. Information such as the distances between tourist attractions، traffic and the start location of the tourist should be considered when deciding about the travel path of the tourist. The goal of tourist path finding is to find a path، through which the tourist can visit all attractions in shortest possible time، considering his priorities، traffic and the distances between attractions. This can be assumed as a spatial optimization problem with such a wide search space that cannot be solved using mathematical and deterministic methods. The goal of this research is to solve this problem using Artificial Bee Colony (ABC) meta-heuristic algorithm. The simulated data of a city with 10 tourist attraction is used for the implementation. At the 350th run of the ABC algorithm the acceptable results are gained. Taking into account the implementation speed، convergence speed and pattern، and the quality of the answers، the algorithm can be accepted as a suitable solution to the tourist path finding problem.