Energy-efficient path planning for a single-load automated guided vehicle in a manufacturing workshop

With the aggravation of the global greenhouse effect and environmental pollution, energy saving and emission reduction have already become the consensus of the manufacturing industry to enhance sustainability. A material handling system is an essential component of a modern manufacturing system, and its energy consumption (EC) is a non-negligible part when evaluating the total production EC. As typical transport equipment, automated guided vehicles (AGVs) have been widely applied in various types of manufacturing workshops. Correspondingly, AGV path planning is usually a multi-objective optimization problem, and closely related to the workshop logistics efficiency and the smoothness of the whole manufacturing process. However, the optimization objectives that current AGV path planning research mostly focuses on are transport distance, time, and cost, while EC or EC-related environmental impact indicators are seldom touched on. To address this, an investigation into the energy-saving oriented path planning is executed for a single-load AGV in a discrete manufacturing workshop environment. Based on the analysis of AGV EC characteristics from the perspective of motion state and vehicle structure, transport distance and EC are selected as two optimization objectives, and an energy-efficient AGV path planning (EAPP) model is formulated. Further, two solution methods, i.e., the two-stage solution method and the particle swarm optimization-based method, are put forward to solve the established model. Moreover, the experimental study verifies the effectiveness of the proposed model and its solution methods and indicates that transport task execution order has a significant impact on AGV transport EC.