Adaptive weighted multi-criteria decision making using modified dijkstra’s algorithm: integrating real-time traffic conditions with hybrid WSM-WPM for dynamic route optimization

Abstract

Traffic congestion is a problem that needs to be solved. A smart route optimization system is needed to overcome this problem, not only using traditional methods but also using algorithms that have the ability to find the shortest route. This study proposes a framework system for multi-criteria decision making that adapts and improves the Dijkstra and weighted product method (WPM) algorithms. The Dijkstra algorithm is modified to be more integrated in solving the fastest travel route, anticipating traffic congestion, improving road safety, saving fuel, and providing real-time data. The weighted sum method (WSM)-WPM hybrid framework has the advantage of WSM additive normalization with the zero-dimensional properties of WPM to overcome different measurement units. Experimental results show a significant reduction in travel time and fuel consumption, as well as an increase in route safety percentage. This system maintains computational efficiency, and this research provides a practical and scalable solution for intelligent transportation systems (ITS), improving the driver experience and overall traffic network safety. The results of the congestion avoidance configuration with the highest hybrid score show a result of 0.4573, yielding a viable alternative route, namely (V1→V3→V6→V9→V12→V14).