Optimal Route Design and Adaptive Route Allocation in Malawi Cities: A Case Study of Lilongwe City.

Urban population in Malawi accounts for 15.3% of the total population with rate of urbanization estimated at 4.2% in the World. Such high reported figures put pressure on the city authorities to provide efficient public services. Specifically, fast urbanization, high population density and rapid growth of vehicle population have put stress on the existing urban transportation system in Lilongwe with more experiences of traffic congestion, high vehicle operating costs and increase in travel times. This creates a demand for efficient routing algorithms to solve these problems popularly known as vehicle routing problems. Addressed as a VRP, the problem of optimizing connections in transportation networks is popular in many different scenarios, such as car journeys, public transportation and logistics. However, to our knowledge, little attention has been paid to such studies in Malawi. Based on Geographic Information System (GIS) and route optimization algorithm, this study proposes a methodology for optimizing route design and allocation of road segments within Lilongwe city subject to congestion effect. Road network data is prepared through digitization process in ArcGIS 10.0 and fed into a modified Dijkstra’s algorithm coded in Java programming language. Shortest routes that are congestion and vehicle operation costs abating are generated and proposed for the road users.

Keywords: Urbanization, Vehicle routing problem (VRP), Dijkstra’s algorithm (DA), Congestion, route optimization, modeling.