Heuristic algorithm for path planning in high-density automated storage and retrieval system raw material box...

Area of Science:

• Industrial Engineering
• Operations Research
• Robotics

Background:

• Automated storage systems reduce costs but face complexity in high-density configurations.
• Optimizing raw material box (RMB) movements in robot-based compact storage and retrieval systems (RCSRS) is an NP-hard problem.
• Reorganization of obstructing boxes significantly impacts storage operation time in RCSRS.

Purpose of the Study:

• To address the AGVs box reorganization path planning problem in AutoStore.
• To develop a mathematical model for optimizing AGV reorganization paths.
• To minimize total AGV operating time during block reshuffling in AutoStore.

Main Methods:

• Formulation of a mathematical model to optimize AGV reorganization paths.
• Development of a heuristic algorithm to optimize the complete order processing workflow.
• Minimization of total operating time for AGVs during block reshuffling.

Main Results:

• The study provides a model to optimize AGV reorganization paths in AutoStore.
• A heuristic algorithm is developed to enhance the complete order processing workflow.
• The proposed methods aim to reduce overall operational time and improve system efficiency.

Conclusions:

• The developed mathematical model and heuristic algorithm effectively address AGV path planning challenges in AutoStore.
• Optimizing reorganization paths significantly reduces operational time in high-density automated storage systems.
• This research contributes to improving the efficiency of robotic storage and retrieval systems.