Itinerary Recommendation Generation using Enhanced Simulated Annealing Algorithm

Abstract The trend of traveling has increased in recent years along with the easy access to information. Travelers create the itinerary before they are travelling to an area. However, creating itinerary is not easy, many factors need to be considered before deciding where to go, such as the “must visited” places in that area, distance between tourist attractions to be visited within a day, preferred tourist attractions, and other information about the places. Generating the optimized distance itinerary is similar as a Traveling Salesman Problem (TSP). The purpose of this research is to study the combination of simulated annealing and Greedy algorithms to create an itinerary. The initialization process of the simulated annealing algorithm uses Greedy algorithm searching technique and then proceeded with existing optimization step in simulated annealing method. This paper proposed a method of enhanced simulated annealing algorithm and the experiment results show the enhanced simulated annealing increase the effectiveness of simulated annealing algorithm which produce the shortest distance needed to travel places around an area.