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Developing Conflict-Free Routes for Automated Guided Vehicles

Author

Listed:
  • Nirup N. Krishnamurthy

    (United Airlines, Chicago, Illinois)

  • Rajan Batta

    (State University of New York at Buffalo, Buffalo, New York)

  • Mark H. Karwan

    (State University of New York at Buffalo, Buffalo, New York)

Abstract

Automated guided vehicles (AGVs) are a highly sophisticated and increasingly popular type of material handling device in flexible manufacturing systems. This paper details solution methodologies for the static routing problem in which demand assignment of the AGVs are known; the focus is to obtain an implementable solution within a reasonable amount of computer time. The objective is to minimize the makespan, while routing AGVs on a bidirectional network in a conflict-free manner. This problem is solved via column generation. The master problem in this column generation procedure has the makespan and vehicle interference constraints. Columns in the master problem are routes iteratively generated for each AGV. The subproblem is a constrained shortest path problem with time-dependent costs on the edges. An improvement procedure is developed to better the solution obtained at the end of the master-subproblem interactions. Several methods of iterating between the master and subproblem are experimented with in-depth computational experiments. Our empirical results indicate that the procedure as a whole usually generates solutions that are within a few percent of a proposed bound, within reasonable computer time.

Suggested Citation

  • Nirup N. Krishnamurthy & Rajan Batta & Mark H. Karwan, 1993. "Developing Conflict-Free Routes for Automated Guided Vehicles," Operations Research, INFORMS, vol. 41(6), pages 1077-1090, December.
    • Handle: RePEc:inm:oropre:v:41:y:1993:i:6:p:1077-1090
    DOI: 10.1287/opre.41.6.1077
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    Cited by:

    1. Ballis, Athanasios & Golias, John, 2002. "Comparative evaluation of existing and innovative rail-road freight transport terminals," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(7), pages 593-611, August.
    2. Chiang, Wen-Chyuan & Kouvelis, Panagiotis & Urban, Timothy L., 2006. "Single- and multi-objective facility layout with workflow interference considerations," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1414-1426, November.
    3. Jenny Nossack & Dirk Briskorn & Erwin Pesch, 2018. "Container Dispatching and Conflict-Free Yard Crane Routing in an Automated Container Terminal," Transportation Science, INFORMS, vol. 52(5), pages 1059-1076, October.
    4. Kaspar Schüpbach & Rico Zenklusen, 2013. "An adaptive routing approach for personal rapid transit," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 371-380, June.
    5. Gamache, Michel & Grimard, Renaud & Cohen, Paul, 2005. "A shortest-path algorithm for solving the fleet management problem in underground mines," European Journal of Operational Research, Elsevier, vol. 166(2), pages 497-506, October.
    6. Dipesh J. Patel & Rajan Batta & Rakesh Nagi, 2005. "Clustering Sensors in Wireless Ad Hoc Networks Operating in a Threat Environment," Operations Research, INFORMS, vol. 53(3), pages 432-442, June.
    7. Hernan Caceres & Rajan Batta & Qing He, 2017. "School Bus Routing with Stochastic Demand and Duration Constraints," Transportation Science, INFORMS, vol. 51(4), pages 1349-1364, November.
    8. Mokhtar, Hamid & Krishnamoorthy, Mohan & Dayama, Niraj Ramesh & Kumar, P.N. Ram, 2020. "New approaches for solving the convoy movement problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    9. Zhuoling Jiang & Xiaodong Zhang & Pei Wang, 2023. "Grid-Map-Based Path Planning and Task Assignment for Multi-Type AGVs in a Distribution Warehouse," Mathematics, MDPI, vol. 11(13), pages 1-20, June.
    10. Tommaso Adamo & Tolga Bektaş & Gianpaolo Ghiani & Emanuela Guerriero & Emanuele Manni, 2018. "Path and Speed Optimization for Conflict-Free Pickup and Delivery Under Time Windows," Transportation Science, INFORMS, vol. 52(4), pages 739-755, August.
    11. R Gopalan & N S Narayanaswamy, 2009. "Analysis of algorithms for an online version of the convoy movement problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1230-1236, September.
    12. Wen-Chyuan Chiang & Panagiotis Kouvelis & Timothy L. Urban, 2002. "Incorporating Workflow Interference in Facility Layout Design: The Quartic Assignment Problem," Management Science, INFORMS, vol. 48(4), pages 584-590, April.
    13. Ram Gopalan, 2015. "Computational complexity of convoy movement planning problems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 82(1), pages 31-60, August.
    14. Ballis, Athanasios & Golias, John, 2004. "Towards the improvement of a combined transport chain performance," European Journal of Operational Research, Elsevier, vol. 152(2), pages 420-436, January.
    15. Min Zhang & Rajan Batta & Rakesh Nagi, 2009. "Modeling of Workflow Congestion and Optimization of Flow Routing in a Manufacturing/Warehouse Facility," Management Science, INFORMS, vol. 55(2), pages 267-280, February.
    16. Wang, Hua & Meng, Qiang & Chen, Shukai & Zhang, Xiaoning, 2021. "Competitive and cooperative behaviour analysis of connected and autonomous vehicles across unsignalised intersections: A game-theoretic approach," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 322-346.
    17. Vis, Iris F.A., 2006. "Survey of research in the design and control of automated guided vehicle systems," European Journal of Operational Research, Elsevier, vol. 170(3), pages 677-709, May.

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