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Home / Archives / Volume-6 / Issue-3 / Article-8

Volume - 6 | Issue - 3 | september 2024

Advanced Route Optimization using Hybrid Algorithms and Road-based Distance Calculation Open Access
Shubham Giri  , Neha Vora  110
Pages: 273-291
Cite this article
Giri, Shubham, and Neha Vora. "Advanced Route Optimization using Hybrid Algorithms and Road-based Distance Calculation." IRO Journal on Sustainable Wireless Systems 6, no. 3 (2024): 273-291
Published
19 October, 2024
Abstract

This study proposes a hybrid approach to route optimization, comparing and combining Genetic Algorithms (GA), Ant Colony Optimization (ACO), and Dynamic Programming (DP) to solve the Traveling Salesman Problem (TSP) and similar routing challenges. The objective is to minimize travel time and cost by incorporating real-time road data from OpenRouteService and Google Maps APIs. The hybrid algorithms are tested on large datasets, demonstrating their scalability and adaptability to real-world complexities such as fluctuating traffic conditions. Through mathematical modelling and pseudocode, the performance of each algorithm is compared, highlighting their effectiveness in optimizing logistics operations. The results indicate that this approach significantly reduces computational time and operational costs, providing a robust solution for modern logistics.

Keywords

Route Optimization Traveling Salesman Problem (TSP) Genetic Algorithms (GA) Ant Colony Optimization (ACO) Dynamic Programming (DP) Haversine Distance OpenRouteService API

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