Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles

Tatsushi Nishi; Yuki Tanaka; Masahiro Inuiguchi

doi:10.1109/COASE.2008.4626458

Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles

Tatsushi Nishi, Yuki Tanaka, Masahiro Inuiguchi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

In this paper, we propose a simultaneous optimization method for task assignment and routing problems for multiple AGVs by decomposition of Petri Nets. In the proposed method, the Petri Net is decomposed into several subnets for task subproblems and AGV subproblems. Each subproblem is solved by Dijkstra's algorithm. The solution of subproblem for each subnet is repeated until a feasible solution for the original problem is obtained. In this study, a new solution method for subproblems with no final marking is developed. The effectiveness of the proposed method is confirmed by comparing the performance with conventional methods.

Original language	English
Title of host publication	4th IEEE Conference on Automation Science and Engineering, CASE 2008
Pages	175-180
Number of pages	6
DOIs	https://doi.org/10.1109/COASE.2008.4626458
Publication status	Published - 2008
Externally published	Yes
Event	4th IEEE Conference on Automation Science and Engineering, CASE 2008 - Washington, DC, United States Duration: Aug 23 2008 → Aug 26 2008

Publication series

Name	4th IEEE Conference on Automation Science and Engineering, CASE 2008

Conference

Conference	4th IEEE Conference on Automation Science and Engineering, CASE 2008
Country/Territory	United States
City	Washington, DC
Period	8/23/08 → 8/26/08

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/COASE.2008.4626458

Cite this

Nishi, T., Tanaka, Y., & Inuiguchi, M. (2008). Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles. In 4th IEEE Conference on Automation Science and Engineering, CASE 2008 (pp. 175-180). Article 4626458 (4th IEEE Conference on Automation Science and Engineering, CASE 2008). https://doi.org/10.1109/COASE.2008.4626458

Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles. / Nishi, Tatsushi; Tanaka, Yuki; Inuiguchi, Masahiro.
4th IEEE Conference on Automation Science and Engineering, CASE 2008. 2008. p. 175-180 4626458 (4th IEEE Conference on Automation Science and Engineering, CASE 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nishi, T, Tanaka, Y & Inuiguchi, M 2008, Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles. in 4th IEEE Conference on Automation Science and Engineering, CASE 2008., 4626458, 4th IEEE Conference on Automation Science and Engineering, CASE 2008, pp. 175-180, 4th IEEE Conference on Automation Science and Engineering, CASE 2008, Washington, DC, United States, 8/23/08. https://doi.org/10.1109/COASE.2008.4626458

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AB - In this paper, we propose a simultaneous optimization method for task assignment and routing problems for multiple AGVs by decomposition of Petri Nets. In the proposed method, the Petri Net is decomposed into several subnets for task subproblems and AGV subproblems. Each subproblem is solved by Dijkstra's algorithm. The solution of subproblem for each subnet is repeated until a feasible solution for the original problem is obtained. In this study, a new solution method for subproblems with no final marking is developed. The effectiveness of the proposed method is confirmed by comparing the performance with conventional methods.

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Petri net decomposition approach for the simultaneous optimization of task assignment and routing with automated guided vehicles

Abstract

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ASJC Scopus subject areas

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