Abstract
India's agriculture sector has shown sustained growth in production levels over time. However, the current production level regarding food storage has not been adequately matched, emphasizing the existing gap in the Indian agricultural cold storage industry. Optimizing the route for cold storage is cost-effective for farmers. The traveling salesperson problem is a well-known algorithmic issue in computer science and operations research, explicitly emphasizing optimization. The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. Computational intelligence algorithms focus on computer techniques that enable machines to improve their performance by analyzing data without explicit programming. Computational intelligence algorithms are employed to address conventional mathematical problems. This research aims to develop connectivity across many cold storage facilities utilizing the traveling salesperson problem algorithm. Various computational intelligence algorithms such as Greedy Algorithm, Simulated Annealing, 2-opt Algorithm, Particle Swarm Optimization, and Ant Colony Optimization are employed to determine the minimum route. The experimental findings demonstrate that the ant colony algorithm yields superior outcomes.