<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To solve the problems of task scheduling and coordination control presented by a multi-AGV system, the mixed regional control model for the production task has been advanced. The architecture of multi-AGV task assignment and scheduling mechanism has been proposed by combining the mixed regional control model for the production task and the neuro-endocrine coordination mechanism. Hormones for manufacturing cell are secreted by the machine tool according to the information in the production task, and the task can be allocated to the most suitable machine according to the hormone concentrations of the manufacturing cell. The AGV’s hormones are secreted according to the AGV’s operation state. The AGV with the largest hormone concentration will be chosen to execute the transportation task, thus shortening the overall run time of the system. A series of scheduling simulation experiments are performed for some specific examples to demonstrate the feasibility and efficacy of the proposed approach. The results show that tasks can be allocated according to the current status of a machine tool and tasks can be scheduled according to the current state of the AGV system to maximize the efficiency of the AGVs as well as that of the overall system.</p>
</abstract>

To solve the problems of task scheduling and coordination control presented by a multi-AGV system, the mixed regional control model for the production task has been advanced. The architecture of multi-AGV task assignment and scheduling mechanism has been proposed by combining the mixed regional control model for the production task and the neuro-endocrine coordination mechanism. Hormones for manufacturing cell are secreted by the machine tool according to the information in the production task, and the task can be allocated to the most suitable machine according to the hormone concentrations of the manufacturing cell. The AGV’s hormones are secreted according to the AGV’s operation state. The AGV with the largest hormone concentration will be chosen to execute the transportation task, thus shortening the overall run time of the system. A series of scheduling simulation experiments are performed for some specific examples to demonstrate the feasibility and efficacy of the proposed approach. The results show that tasks can be allocated according to the current status of a machine tool and tasks can be scheduled according to the current state of the AGV system to maximize the efficiency of the AGVs as well as that of the overall system.

Multi-Agv Scheduling Optimization Based on Neuro-Endocrine Coordination Mechanism

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

To solve the problems of task scheduling and coordination control presented by a multi-AGV system, the mixed regional control model for the production task has...

Multi-Agv Scheduling Optimization Based on Neuro-Endocrine Coordination Mechanism

Data publikacji: 01 gru 2014

Zakres stron: 1613 - 1630

Otrzymano: 14 sie 2014

Przyjęty: 03 lis 2014

DOI: https://doi.org/10.21307/ijssis-2017-723

Słowa kluczowe
multi-AGV, scheduling strategy, coordination control, neuro-endocrine coordination mechanism, scheduling simulation

© 2014 Qixiang Cai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Multi-Agv Scheduling Optimization Based on Neuro-Endocrine Coordination Mechanism

Data publikacji: 01 gru 2014

Zakres stron: 1613 - 1630

Otrzymano: 14 sie 2014

Przyjęty: 03 lis 2014

DOI: https://doi.org/10.21307/ijssis-2017-723

Słowa kluczowemulti-AGV, scheduling strategy, coordination control, neuro-endocrine coordination mechanism, scheduling simulation

© 2014 Qixiang Cai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
multi-AGV, scheduling strategy, coordination control, neuro-endocrine coordination mechanism, scheduling simulation