TY - JOUR
T1 - A simulation study on the performance of task-determination rules and delivery-dispatching rules for multiple-load AGVs
AU - Ho, Y. C.
AU - Chien, S. H.
PY - 2006/10/15
Y1 - 2006/10/15
N2 - In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here.
AB - In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here.
KW - Computer simulation
KW - Delivery-dispatching rule
KW - Multiple-load AGV
KW - Task-determination rule
KW - Vehicle dispatching
UR - http://www.scopus.com/inward/record.url?scp=33748518593&partnerID=8YFLogxK
U2 - 10.1080/00207540500442401
DO - 10.1080/00207540500442401
M3 - 期刊論文
AN - SCOPUS:33748518593
SN - 0020-7543
VL - 44
SP - 4193
EP - 4222
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 20
ER -