Abstract
Automated Material Handling System (AMHS) plays a key role in factory automation. Vehicle feet sizing is one of the critical issues when designing an effective AMHS. However, due to complexity of AMHS design and uncertainty involved in the production process, e.g., random processing time, vehicle feet sizing is a challenging problem, especially when there are multi-objectives, e.g., minimized cycle times and maximized throughputs are simultaneously desired. In this paper, we propose a novel framework which integrates simulation optimization techniques and Data Envelopment Analysis (DEA) to facilitate the identifi cation of the optimal feet sizes of AMHS under multiple objectives. The trade-o s between diff erent objectives can also be demonstrated. A numerical study shows that the proposed framework can outperform the traditional approaches. In addition, an empirical study at the end verifies the effectiveness and the viability of the proposed framework in practical settings.