Modified A* Algorithm integrated with ant colony optimization for multi-objective route-finding; case study: Yazd

Abstract

In this paper, MASA (Modified A* Algorithm) method is introduced which can merge numerous factors with different weights into a multi-weighted graph to offer the most optimal route for a pedestrian tourist. Several mobile applications support personalized tour recommendations in making feasible plans, however, tours should not only make visiting attractions possible via the shorter route but also satisfy the unique needs of individuals with different preferences. MASA integrates the Ant Colony Optimization algorithm for arranging points of interest (POI), with a modified A* algorithm for generating multi-weighted graphs through pairs of POIs to propose the most suitable tour and facilitate traversal for a tourist who does not get involved with riding vehicles. Our contribution in this research is to consider multiple factors simultaneously or customize the route based on the user’s choice, and introduce pareto front chart for selecting optimal links, which has not been solved yet for being a challenging as well as complicated case. The user in this paper is authorized to choose preferred POIs, defined the importance of each parameter to affect route finding. A historical region in Yazd is selected as the case study due to its winding streets to show the solidity of our approach, with four main factors including Length, Communion, Relaxation, and Isovist, and then three routes have been generated considering customized selections along with an overall route considering all objectives. The computational results have shown the capability of the new proposed algorithm in route finding.