Dynamic storage planning and control in a warehouse wtih robotic equipment
Among warehouse activities, order picking is the most time consuming and labor-intensive activity. Robotic equipment and techniques have been applied to the warehouse to increase the efficiency. The growing complexity in coordinating the flow of materials, as well as the information among the related departments, have raised the challenges in the dynamic planning and control of the warehouse. Recent developments in increasing the efficiency of warehouse activities show a variety of solutions, but need further systematic solution and consideration of the adaptability of the environment and equipment. The purpose of the present study was to investigate the dynamic planning and control algorithms on automated warehouse in supply network, and to survey the applied robotic equipment and control algorithms. A case problem is introduced as the background of the warehouse management system. Inspired by the previous research in finding the solution to improve the warehouse operation efficiency, a traditional and data mining combined protocol is proposed and formulated into a mathematical problem. Then a bio-inspired approach is used to solve the storage optimization problem. Experiments are done to prove that improvements of storage efficiency range from 47% to 730% compared with traditional method. In the second part of the thesis,a framework of warehouse problems is constructed to show the compatibility of the robotic equipment and algorithms. An analogy of robotic simple assembly problem, bin assignment problem, and pick-insert sequence are used to compare with the navigation planning problem, robotic forklift for intelligent warehouse problem. The thesis expanded the warehouse problems categorization into four subsection with respective of algorithms used to solve the problem. Then a survey of robotic equipment is conduced to study the assumptions that is needed for certain type of problems and its impact on the performance compared with the performance from traditional practices in industry. Several main stream robotic equipment survey include: AGVs, RFID in vision for intelligent warehouse, flying robots, unmanned aerial vehicles. Algorithms surveyed include routing, path planning, A* algorithms, and extended Kalman Filter. Compared with traditional approach in warehouse management, the proposed DSAP-GA achieves a better performance and the robotic algorithm and equipment survey serves as a complementation of the research in creating a highly effective automated warehouse environment, therefore a better control for the entire supply network.
Nof, Purdue University.
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