Assignment First Routing Second (AFRS) Algorithm for City Logistics

Abstract

Transport of goods is one of the critical elements for supporting economic development in an urban area. There are several issues related to the transportation of goods in the city, e.g. environmental and energy issue. With the problems of transportation of products in the urban area, the concept of city logistics was introduced. One of the city logistics solutions is the use of various types of vehicles to transport products, including small vehicles. This study develops an assignment first routing second (AFRS) algorithm to solve the heterogeneous vehicle routing problems in the context of city logistics. The algorithm is divided into two mathematical models; i.e. assignment problem and travelling salesman problem. The branch-and-bound method is used for solving those problems. In this research, there are many types of vehicles used to deliver goods to consumers in the urban area. The algorithm considers the level of congestion in the customer area. The main purpose of the algorithm is to make the right assignments, so the small vehicles can be optimally assigned to serve customers, especially in congested areas, but do not exceed their vehicle capacity. Then, this research determines the most optimal route with the objective function is to minimize the total distance travelled by each vehicle. This study used hypothetical data to test and verify the algorithm. Seven data instances are developed with the number of customers are ranged from 20 to 80 customers, also with various type and amount of vehicles for each case. From the computational results, the algorithm successfully found the optimal assignments strategy for six datasets. In that strategy, the small vehicles are optimally assigned to serve as many customers as possible, especially for customers in congested areas. The optimal route for each vehicle is also found with the travelling salesman problem (TSP) model.