Title: Automated guided vehicle dispatching based on combinatorial optimisation to minimise job waiting time on shop floors

Authors: Shiyang Huang; Guiping Hu

Addresses: Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, 50011, USA ' Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, 50011, USA

Abstract: On manufacturing shop floors, automated guided vehicles (AGVs) have been widely adopted and configured for material handling, and they are dispatched to transport jobs between work centres. In this paper, two AGV dispatching strategies based on combinatorial optimisation are proposed. AGVs are assigned to work centres according assignment optimisation models to minimise the total waiting time of jobs. In the decision horizon, status of AGVs and jobs in or between work centres are predicted. The AGV dispatching strategies take future transportation requests into consideration and optimally configure transportation resources, such that material handling can be more efficient than those adopting classic AGV assignment rules in which only the current request is considered. The strategies were demonstrated in a case study and compared with classic AGV assignment rules including random assignment and nearest vehicle/shortest travel time rule. The results showed that the proposed dispatching strategies could better control job waiting time on the shop floors compared to classic AGV assignment rules.

Keywords: AGV dispatching; combinatorial optimisation; job waiting time minimisation; assignment problem.

DOI: 10.1504/IJPS.2019.103016

International Journal of Planning and Scheduling, 2019 Vol.3 No.1, pp.28 - 46

Received: 18 Apr 2018
Accepted: 04 Jan 2019

Published online: 11 Oct 2019 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article