This paper presents an optimized delivery route planning system using a hybrid approach of Dijkstra’s algorithm and heuristicmethods to address the Travelling Salesman Problem (TSP). The objective is to find the most efficient route for a delivery agent in a fooddelivery scenario using the Zomato delivery analytics dataset. The system integrates Dijkstra's algorithm with the Greedy Nearest Neighborstrategy and compares it with Ant Colony Optimization (ACO) and Genetic Algorithm (GA). A comparative analysis of route accuracy,performance time, computational complexity, and scalability is discussed. The proposed system demonstrates significant improvement inroute optimization, particularly for dynamically changing environments with multiple constraints. Visualization of route paths andperformance metrics confirms the benefits of integrating classical and nature-inspired algorithms in a hybrid framework.Keywords: Travelling Salesman Problem, Dijkstra’s Algorithm, ACO, GA, Route Optimization, Zomato Dataset, Logistics, HybridOptimization