Multiobjective route selection for car navigation system using genetic algorithm

Abstract

Route planning is an important problem for a car navigation system. Given a set of origin-destination pair, there could be many possible routes for a driver. Search for shortest route from one point to another on a weighted graph is a well known problem and has several solutions like Dijkstra algorithm, Bellman-Ford algorithm etc. But in case of car navigation systems the shortest path may not be the best one from the point of view of driver's satisfaction. So, for a practical car navigation system in dynamical environment, we need to specify multiple and separate good (near optimal) choices according to multiple criteria which make the search space too large to find out the solution in real time by deterministic algorithms. Genetic algorithms (GA) are now widely used to solve search problems with applications in practical routing and optimization problems. GA includes a variety of quasi optimal solutions, which can be obtained in a given time. In this work we propose a GA based algorithm to find out simultaneously several alternate routes depending on different criterion according to driver's choice such as shortest path by distance, path which contains minimum number of turns, path passing through mountains or by the side of a river etc. The proposed algorithm has been evaluated by simulation experiment using real road map compared to other existing GA based algorithms. It has been found that the proposed algorithm is quite efficient in finding alternate non overlapping routes with different characteristics.