Travelling salesman problem using genetic algorithm / Muhammad Faiz Wafiq Mohd Zaini, Nurin Hannani Mohd Bakhary and Nur Aishah Zakaria

Travelling Salesmen Problem is a well-known algorithm problem in the fields of computer science and operation research. This paper evaluates the Travelling Salesmen Problem based on dataset used from (Ohlmann & Thomas, 2007) and this research 30 towns that mentioned from (Ohlmann & Thomas, 2007). Travelling salesmen must travel to every towns and ends at the same town when it started. Nowadays, the demand for salesmen deliver increase so frequency salesmen travel a lot and need to finds ways to make fast deliveries. Thus, the aim of the study is to help the delivering sector in overcoming the problems of delivering goods to customers while minimizing distance travelled. The method that use in this research is Genetic Algorithm. The first round this research use two Genetic Algorithms’ operator which are crossover and inversion operator. The second round this research use three operator which are crossover, inversion and mutation operator. The parents that used in every section are same. After each operation, the total distance was determine and the least total distance will be chosen. This research stop after 10 iteration which in both round. In each iteration, the selection step compare and select the minimum distance for each chromosome. The result shows using Genetic Algorithm operator can help Travelling Salesmen to minimize the distance effectively and to make it more effective Travelling Salesmen need to use three Genetic Algorithms’ operator. In conclusion, companies deliver sector can apply this research in their companies to decrease their logistic costs.