20.500.12556/DKUM-96064 Improving AGV path planning efficiency using Genetic Algorithms with Hamming distance-based initialization This paper presents a Genetic Algorithm (GA) framework for warehouse navigation as a Travelling Salesman Problem (TSP) variant for Automated Guided Vehicles (AGVs). The warehouse layout is represented as a graph, where pick-up locations serve as terminal nodes. A distance matrix, computed via Breadth-First Search (BFS) enables efficient route evaluation. To promote diversity in the initial population, a Hamming distance-based vectorized initialization strategy is employed, ensuring that the chromosomes are maximally distinct. The GA balances exploration and exploitation by dynamically adjusting the fitness function. Early generations emphasize diversity, while later ones focus on solution refinement, improving convergence and avoiding premature stagnation. Our key contribution demonstrates that the Hamming distance-based approach achieves comparable or better results with significantly fewer chromosomes. This reduces computational cost and runtime, making the method well-suited for real-time AGV routing in warehouses. The framework is adaptable to structured environments and shows strong potential for integration into real-world logistics and robotics applications. Future work will focus on optimizing the algorithm and integrating it into the ROS 2 environment. automated guided vehicles (AGV) warehouse routing combinatorial optimization Hamming distance initialization Robot operating system 2 (ROS 2) avtomatsko vodena vozila usmerjanje v skladišču genetski algoritmi kombinatorična optimizacija inicializacija Hammingove razdalje Robotski operacijski sistem 2 (ROS 2) genetsko programiranje true false true University of Maribor Angleški jezik Slovenski jezik https://apem-journal.org/Archives/2025/Abstract-APEM20-3_299-308.html Članek v reviji 2025-11-28 13:47:55 2025-11-28 13:47:55 2026-01-22 08:15:27 0000-00-00 00:00:00 2025 0 0 str. 299-308 no. 3 Vol. 20 Sept. 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-07-06 2025-10-24 2025-10-28 007.52:519.6 257509123 10.14743/apem2025.3.541 1855-6531 APEM20-3_299-308.pdf APEM20-3_299-308.pdf 1 E405F25849B90E7AF8AB4A6A00386B22 dc70c473c34cdc43f7a44c1b7fe75730fe47681eb1c55389261d136e71cfb22e c5ce69f1-cc58-11f0-b6ed-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=200951 https://apem-journal.org/Archives/2025/Abstract-APEM20-3_299-308.html 0 cb923d85-cc58-11f0-b6ed-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=200952 Fakulteta za strojništvo Advances in production engineering & management 0 0 0