| dc.description.abstract | Order picking in warehouses has the highest total operating costs compared to other activities, which is 35% of the total cost, on the other side the development of smart warehouses in the world is very fast. This has led to the emergence of many technological innovations for order picking such as RMFS to optimize order picking. The purpose of this study is to design an RMFS path planning scenario with the development of the A* algorithm to increase warehouse throughput by minimizing deceleration acceleration and avoiding collisions. The development of the A* algorithm is done by modifying the objective function by adding a turning factor element and modifying the calculation for the distance of the point (n) to the endpoint. RMFS path planning is done by programming and simulation with NetLogo. The best scenario for path planning with the A* algorithm has a benchmark in the form of simulation results that have the highest throughput rate for RMFS operations in the warehouse. The results of the research in the form of the best scenario to handle 5000 SKU is a rule-based system with 50 robot units. However, with the appropriate penalty parameters, the best scenario obtained is a modified A* algorithm robot movement system with a penalty value that handles 5000 SKUs with 10 robot units. The advantage of implementing rule-based system scenario has an average throughput value of 1117 items for 1 hour. Meanwhile, the best A* algorithm scenario with penalty value has an average throughput value of 1058 items for 1 hour. | en_US |
