Implementation of the Particle Swarm Optimization Algorithm on an Arduino Microcontroller Based AS/RS

Abstract

Manual warehouse systems in Indonesia cause tracking and storage issues, increasing the risk of damage. Implementing Particle Swarm Optimization (PSO) in Automated Storage and Retrieval Systems (AS/RS) can optimize travel paths, reduce errors, and enhance storage efficiency. Parameters such as particles, iterations, and inertia are applied in this system. This study integrates PSO with Arduino-based AS/RS using the VDI 2206 method, with AS/RS racks designed in a 4x4 matrix. In various case studies, PSO successfully reduced travel distances by 1% to 32% and operational time by 5% to 21%. PSO effectively enhances the operational efficiency of AS/RS by optimizing travel routes, thereby reducing the time needed for storage and retrieval operations. Additionally, it is important to note that the reduction in travel distance is influenced by the initial input addresses without PSO, which might already be near optimal. Thus, while PSO significantly improves efficiency, the extent of reduction can vary based on how close the initial input addresses without PSO are to the optimal route.