A simulation-based comparative study of component allocation strategies in AGV-supported assembly intralogistics

Abstract

This study addresses the problem of resource management in assembly intralogistics systems integrating human operators and autonomous guided vehicles (AGVs). Despite the growing interest in hybrid intralogistics systems, there is a limited number of studies that simultaneously consider storage allocation strategies, AGV configuration, and human resource involvement within a unified simulationoptimization framework. The objective of this study is to evaluate the effectiveness of alternative component allocation strategies and to support decision-making in hybrid intralogistics systems. A simulation model developed in the FlexSim environment represents a simplified assembly hall including a storage area and assembly stations. Two variants were analyzed: a baseline scenario with random allocation of storage locations and an optimized scenario using a multi-criteria optimization approach implemented with OptQuest. The experiments considered different system configurations, including the number and capacity of AGVs, storage allocation policies, and operator availability. The results show that random allocation leads to significant variability in transport performance and resource utilization, while the optimized variant improves system stability and predictability. The optimization process revealed trade-offs between transport efficiency and operational costs, indicating the need to balance AGV usage and human labor. The findings provide insights into the design and evaluation of hybrid intralogistics systems and highlight the importance of coordinated resource management. At the same time, the study acknowledges its limitations resulting from the use of simplified assumptions and hypothetical data.