Hybrid model of taxonomy and genetic algorithms for finding shortest path in transportation systems

Abstract

This is research is aimed at elaborating a new methodology of shortest path finding by utilizing the methods of taxonomy and genetic algorithms. Combination of the two is developed and called Genetic Taxonomy Evaluator (GTE) which is expected to be an alternative tool to solve shortest path finding problems within the transportation networks While keeping the properties of transportation networks Taxonomy Reconstructor (TR) transforms the network representation into taxonomic structure, which is hierarchically shaped, based on problem to be solved. In the process TR also creates classification of nodes in the network. This classification provides facilities to isolate the problem to the core, and the criteria that can be inserted in the Genetic Algorithm (GA). A package program for GTE is then developed in C‐Language and performance of model is analyzed upon a medium scale of Sioux‐Falls City Network. In conclusion, it is found that to achieve fairly quick convergence of GTE computation several optimal parameters of GA should be determined prior to searching for the shortest paths. And since GTE has only been applied to limited case, it is suggested that the findings could be a threshold for further researches.

Development of realistic shortest path algorithm considering lane changes

“…The shortest path problem (SPP) has long been studied in transportation planning and advanced traveler information systems area [1][2][3][4][5][6]. The problems dealing with the least-time path on the basis of real-time traffic information are becoming popular.…”