Comparative Analysis of Evolutionary Algorithms for Optimizing Vehicle Routing in Smart Cities

Abstract

This paper presents a comparative analysis of evolutionary algorithms, including genetic algorithms, particle swarm optimization, cuckoo algorithm, and the Harris Hawk Optimization algorithm, for optimizing vehicle routing in smart cities. The study evaluates the performance of these algorithms in minimizing costs and maximizing efficiency in the context of providing services to requesters. Results indicate the effectiveness of the Harris Hawk Optimization algorithm compared to other approaches, suggesting its suitability for real-world applications in smart city environments. Future directions for research in this area are also discussed.