The number of culinary attractions in Malang that can be reached makes it difficult for culinary lovers to find the optimum route, in terms of distance, time, and cost to travel from one place to another. One of the factor that influence people's when they did culinary tour is the transportation fees. A thing that is very relate with transportation is the distance. Many culinary lovers feel like they have wasting their time to get to the place they want because they choose the wrong routes. Since Malang has so many culinary attractions, it takes optimization in searching the optimum route from starting point to the destination point. The bee colony algorithm was chosen because the algorithm is considered to have the ability to exit local minimum and can be efficiently used for optimization. Bee colony algorithm also can solve the problem of Traveling Salesman Problem better than other algorithm which is also based on group intelligence. At the experiment we can conclude that bee colony algorithm has converged in the search for the best solution that can be seen from the fitness resulted. One of the best have been convergence in bee colony at 20 of 50 bee colony amounts. In addition the convergence can also be seen on the number of iterations at 20 of the maximum number of iterations 50.
Copyrights © 2017