Abstract
Finding the shortest travelling distance based on various situations might assist travelers in making a better selection of route decisions. The main goal of this paper is to solve the routing problem for the company’s fleet vehicle (XpressBees) in order to find the best route under various constraints such as Signalized Intersections, Vehicle Capacity, Customer Demands, and Time Windows in order to reduce transportation costs by using real data. TSP and VRP and their variants are common problems for logistics companies that handle commodities transportation. In addition, for signalised intersections, the Highway Capacity Manual is used, and for truck optimization, the Product Loading Algorithm is used. As a result, there are various algorithms that provide a solution to this problem, such as the Branch and Bound Penalty Method, Dijikstra’s Algorithm, Dynamic Programming, Clarke and Wright savings algorithm and Holmes and Parker Heuristic. These algorithm returns the best option, which is the cheapest route.