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On routing and scheduling a fleet of resource-constrained vessels to provide ongoing continuous patrol coverage

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Abstract

The objective of the Patrol Boat Scheduling Problem with Complete Coverage (PBSPCC) is to find a minimum size patrol boat fleet to provide continuous coverage at a set of maritime patrol regions, ensuring that there is at least one vessel on station in each patrol region at any given time. The requirement for continuous patrol coverage is complicated by the need for vessels to be replenished on a regular basis. This combinatorial optimization problem contains both routing and scheduling components and is known to be NP-hard. In this paper, we show how recent theoretical insights can be used in conjunction with specially tailored heuristics to accelerate a column generation solution approach over a resource-space-time network construct. We show how the column generation approach can be used within a branch-and-price framework and combined with various reduction techniques to find cyclic and long-term scheduling solutions on a range of test problems.

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References

  • Ahuja, R., Magnanti, T., & Orlin, J. (1993). Network flows: Theory, algorithms, and applications. Prentice Hall.

  • Akca, Z., Ralphs, T. K., & Berger, R. T. (2010). Solution methods for the multi-trip elementary shortest path problem with resource constraints. Optimization Online. http://www.optimization-online.org/DB_HTML/2011/03/2962.html.

  • Andersen, J., Christiansen, M., Crainic, T. G., & Grønhaug, R. (2011). Branch and price for service network design with asset management constraints. Transportation Science, 45(1), 33–49.

    Article  Google Scholar 

  • Barnhart, C., Johnson, E. L., Nemhauser, G. L., Savelsbergh, M. W. P., & Va, P. H. (1998). Branch-and-price: Column generation for solving huge integer programs. Operations Research, 46(3), 316–329.

    Article  Google Scholar 

  • Ben Amor, H., & Valério de Carvalho, J. (2005). Cutting stock problems. In G. Desaulniers, J. Desrosiers, & M. M. Solomon (Eds.), Column generation (pp. 131–161). Springer.

  • Brown, G. G., Dell, R. F., & Farmer, R. A. (1996). Scheduling Coast Guard district cutters. Interfaces, 26(2), 59–72.

    Article  Google Scholar 

  • Çapar, İ., Keskin, B. B., & Rubin, P. A. (2015). An improved formulation for the maximum coverage patrol routing problem. Computers & Operations Research, 59, 1–10.

  • Chircop, P. A. (2017). Column generation approaches to patrol asset scheduling with complete and maximum coverage requirements (Doctoral dissertation, University of New South Wales). https://doi.org/1959.4/57656

  • Chircop, P. A., & Surendonk, T. J. (2021). On integer linear programming formulations of a patrol boat scheduling problem with complete coverage requirements. The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 18(4), 429–439.

    Article  Google Scholar 

  • Chircop, P. A., Surendonk, T. J., van den Briel, M. H. L., & Walsh, T. (2013). A column generation approach for the scheduling of patrol boats to provide complete patrol coverage. In J. Piantadosi, R. S. Anderssen, & J. Boland (Eds.), Proceedings of the 20th international congress on modelling and simulation (pp. 1110–1116). Modelling and Simulation Society of Australia and New Zealand.

  • Chircop, P. A., Surendonk, T. J., van den Briel, M. H. L., & Walsh, T. (2021). A branch-and-price framework for the maximum covering and patrol routing problem. In A. T. Ernst, S. Dunstall, R. García-Flores, M. Grobler, & D. Marlow (Eds.), Data and decision sciences in action 2 (pp. 59–80). Springer.

  • Christiansen, M., Fagerholt, K., & Ronen, D. (2004). Ship routing and scheduling: Status and perspectives. Transportation Science, 38(1), 1–18.

    Article  Google Scholar 

  • Christiansen, M., & Nygreen, B. (1998). A method for solving ship routing problems with inventory constraints. Annals of Operations Research, 81, 357–378.

    Article  Google Scholar 

  • Chvatal, V. (1983). Linear programming. Macmillan.

  • Conforti, M., Cornuéjols, G., & Zambelli, G. (2014). Integer programming. Springer.

  • Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to algorithms (3rd edn.). The MIT Press.

  • Dantzig, G. B., & Wolfe, P. (1960). Decomposition principle for linear programs. Operations Research, 8(1), 101–111.

    Article  Google Scholar 

  • Darby-Dowman, K., Fink, R. K., Mitra, G., & Smith, J. W. (1995). An intelligent system for US Coast Guard cutter scheduling. European Journal of Operational Research, 87(3), 574–585.

    Article  Google Scholar 

  • Desaulniers, G., Desrosiers, J., & Solomon, M. M. (2002). Accelerating strategies in column generation methods for vehicle routing and crew scheduling problems. In Essays and surveys in metaheuristics (pp. 309–324). Springer.

  • Desrochers, M. (1986). La fabrication d’horaires de travail pour les conducteurs d’autobus par une méthode de génération de colonnes (Unpublished doctoral dissertation). Centre de Recherche sur les Transports, Université de Montréal.

  • Desrochers, M., & Soumis, F. (1988). A generalized permanent labeling algorithm for the shortest-path problem with time windows. Information Systems and Operations Research, 26(3), 191–212.

    Article  Google Scholar 

  • Dewil, R., Vansteenwegen, P., Cattrysse, D., & Oudheusden, D. V. (2015). A minimum cost network flow model for the maximum covering and patrol routing problem. European Journal of Operational Research, 247(1), 27–36.

    Article  Google Scholar 

  • Easton, K., Nemhauser, G., & Trick, M. (2004). CP based branch-and-price. In M. Milano (Ed.), Constraint and integer programming (pp. 207–231). Springer.

  • Fang, F., Stone, P., & Tambe, M. (2015). When security games go green: Designing defender strategies to prevent poaching and illegal fishing. In Proceedings of the 24th international joint conference on artificial intelligence (pp. 2589–2595). AAAI Press.

  • Fischetti, M., Lodi, A., Martello, S., & Toth, P. (2001). A polyhedral approach to simplified crew scheduling and vehicle scheduling problems. Management Science, 47(6), 833–850.

    Article  Google Scholar 

  • Ford, L. R., & Fulkerson, D. R. (1958). A suggested computation for maximal multi-commodity network flows. Management Science, 5(1), 97–101.

    Article  Google Scholar 

  • Gilmore, P. C., & Gomory, R. E. (1961). A linear programming approach to the cutting-stock problem. Operations Research, 9(6), 849–859.

    Article  Google Scholar 

  • Gualandi, S., & Malucelli, F. (2009). Constraint programming-based column generation. 4OR, 7(2), 113–137.

  • Hahn, R. A., & Newman, A. M. (2008). Scheduling United States Coast Guard helicopter deployment and maintenance at Clearwater Air Station, Florida. Computers & Operations Research, 35(6), 1829–1843.

  • He, F., & Qu, R. (2012). A constraint programming based column generation approach to nurse rostering problems. Computers & Operations Research, 39(12), 3331–3343.

  • Horn, M. E. T., Jiang, H., & Kilby, P. (2006). Scheduling patrol boats and crews for the Royal Australian Navy. Journal of the Operational Research Society, 58(10), 1284–1293.

    Article  Google Scholar 

  • Hsieh, Y. C., You, P. S., Lee, P. J., & Lee, Y. C. (2015). A novel encoding scheme based evolutionary approach for the bi-objective grid patrol routing problem with multiple vehicles. Scientia Iranica. Transaction B, Mechanical Engineering, 22(4), 1576–1585.

    Google Scholar 

  • Irnich, S., & Desaulniers, G. (2005). Shortest path problems with resource constraints. In G. Desaulniers, J. Desrosiers, & M. M. Solomon (Eds.), Column generation (pp. 33–65). Springer.

  • Keskin, B. B., Li, S., Steil, D., & Spiller, S. (2012). Analysis of an integrated maximum covering and patrol routing problem. Transportation Research Part E: Logistics and Transportation Review, 48(1), 215–232.

    Article  Google Scholar 

  • Kim, J., Song, B. D., & Morrison, J. R. (2013). On the scheduling of systems of UAVs and fuel service stations for long-term mission fulfillment. Journal of Intelligent & Robotic Systems, 70(1–4), 347–359.

  • Lübbecke, M. E. (2001). Engine scheduling by column generation (Doctoral dissertation). Braunschweig University of Technology. https://doi.org/10.24355/dbbs.084-200511080100-720

  • Lübbecke, M. E., & Desrosiers, J. (2005). Selected topics in column generation. Operations Research, 53(6), 1007–1023.

    Article  Google Scholar 

  • Millar, H. H., & Russell, S. N. (2012). A model for fisheries patrol dispatch in the Canadian Atlantic offshore fishery. Ocean & Coastal Management, 60, 48–55.

  • Nemhauser, G. L., & Wolsey, L. A. (1988). Integer and combinatorial optimization. Wiley.

  • Nulty, W. G., & Ratliff, H. D. (1991). Interactive optimization methodology for fleet scheduling. Naval Research Logistics, 38(5), 669–677.

    Article  Google Scholar 

  • Shieh, E., Jain, M., Jiang, A. X., & Tambe, M. (2013). Efficiently solving joint activity based security games. In Proceedings of the 23rd international joint conference on artificial intelligence (pp. 346–352). AAAI Press.

  • Smith, O. J., Boland, N., & Waterer, H. (2012). Solving shortest path problems with a weight constraint and replenishment arcs. Computers & Operations Research, 39(5), 964–984.

  • Surendonk, T. J., & Chircop, P. A. (2020a). Detailed complexity proofs for the patrol boat scheduling problem with complete coverage (Technical note no. DST-Group-TN-2026). Canberra, Australian Capital Territory: Joint and Operations Analysis Division, Defence Science and Technology Group.

  • Surendonk, T. J., & Chircop, P. A. (2020b). On the computational complexity of the patrol boat scheduling problem with complete coverage. Naval Research Logistics, 67(4), 289–299.

  • Vanderbeck, F. (1994). Decomposition and column generation for integer programs (Doctoral dissertation). Universite Catholique de Louvain. https://doi.org/2078.1/205381

  • Vanderbeck, F. (2000). On Dantzig–Wolfe decomposition in integer programming and ways to perform branching in a branch-and-price algorithm. Operations Research, 48(1), 111–128.

    Article  Google Scholar 

  • Vanderbeck, F. (2005). Implementing mixed integer column generation. In G. Desaulniers, J. Desrosiers, & M. M. Solomon (Eds.), Column generation (pp. 331–358). Springer.

  • Wagner, M. R., & Radovilsky, Z. (2012). Optimizing boat resources at the US Coast Guard: Deterministic and stochastic models. Operations Research, 60(5), 1035–1049.

    Article  Google Scholar 

  • Zadeh, H. S., Storey, I., & Lenarcic, J. (2009). NaMOS; Scheduling patrol boats and crews for the Royal Australian Navy. In 2009 IEEE aerospace conference (pp. 1–12).

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Acknowledgements

Paul Chircop would like to acknowledge his co-authors for their expert supervision of his doctoral studies from 2010–2016 at the University of New South Wales. Paul Chircop and Timothy Surendonk wish to thank Dr Maria Athanassenas (Group Leader Maritime Mathematical Sciences, Joint and Operations Analysis Division) of the Defence Science and Technology Group for her generous encouragement and support. Toby Walsh was funded by the European Research Council under the Horizon 2020 Programme via AMPLify 670077.

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Chircop, P.A., Surendonk, T.J., van den Briel, M.H.L. et al. On routing and scheduling a fleet of resource-constrained vessels to provide ongoing continuous patrol coverage. Ann Oper Res 312, 723–760 (2022). https://doi.org/10.1007/s10479-021-04474-6

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