Genetic Algorithm for Logistics-Route Optimization in Urban Area

This paper presents an optimal solution of logistics-route planning especially in urban areas. This study is motivated by a significant increment of parcel deliveries due to the fast growing e-commerce sector. The parcel deliveries are a logistics activity, where transportation is one of the main concerns. The transportation gives a significant contribution to the logistics cost such that minimising it is desired. The transportation cost can be reduced through several methods and one of them is minimizing the travel distance. There are many route options for delivering the parcels but not all of them are the minimum-distance route. Finding the minimum-distance route is an optimization problem which is not an easy problem. In this study, the genetic algorithm (GA) is applied to obtain the optimal route which is the shortest distance route. A case study of planning a route for delivering 20 parcels in Tangerang Selatan City is presented. The route planning and GA are implemented in a computer program written in Python. Executing the program resulted in an optimal route represented in a map visualization and the total distance. The optimal route was obtained through 800 iterations which were completed in less than one minute of computation.