A Library Review Study: Conceptual Model for Maritime Inventory-Routing Problem

Document Type : Review Paper

Authors

Faculty of Economics, Kharazmi University, Tehran, Iran

Abstract

The main focus of this paper is presenting a conceptual structure for Maritime Inventory-Routing Problem. We have looked at the matter from the supply chain angel and summed up the main comprising elements and major hypotheses in the framework of a conceptual model. We have surveyed in details the related literature in a classified manner, separated various issues and eventually in accordance with the identified vacuums, presented the grounds for development in the same particular framework. What we deal with in this article is in fact the zero level of the for Maritime Inventory-Routing Problem while for focusing on higher levels it is possible to deal with greater details by providing arithmetic models on more comprehensive navigation of naval goods in a more compact and sold manner. According to this review most of researches are deterministic at the tactical level, on the basis of discreet time and in the arc-flow framework, generally solved by exact or heuristic methods.

Keywords

Main Subjects

References

Arijit Dea, Sri Krishna Kumara, Angappa Gunasekaranb and Manoj Kumar Tiwaria (2017), Sustainable maritime inventory routing problem with time window, Engineering Applications of Artificial Intelligence, Vol. 61, pp. 77–95
Agra, A., Christiansen, M., Hvattum, L. and Rodrigues, F. (2016). A MIP Based Local Search Heuristic for a Stochastic Maritime Inventory Routing Problem. Springer International Publishing Switzerland, pp. 18-34
Agra, A., Christiansen, M., Delgado, A. and Hvattum, L. M. (2015). A maritime inventory routing problem with stochastic sailing and port times. Computer and operations research. Vol. 61, pp. 18–30.
Agra, A., Andersson, H., Christiansen, M., and Wolsey, L. (2013a). A maritime inventory routing problem: Discrete time formulations and valid inequalities. Networks, Vol. 62(4), pp. 297–314.
Agra, A., Christiansen, M., and Delgado, A. (2013b). Mixed integer formulations for a short sea fuel oil distribution problem. Transportation Science, Vol. 47(1), pp. 108–124
Agra, A., Christiansen, M., Figueiredo, R., Hvattum, L.M., Poss, M. and Requejo, C. (2013c). The robust vehicle routing problem with time windows. Computer and operations research. Vol.  40, pp. 856–866.
Al-Khayyal, F. and Hwang, S. (2007). Inventory constrained maritime routing and scheduling for multi-commodity liquid bulk, part i: applications and model. European Journal of Operational Research, Vol. 176, pp. 106–130.
Al-Haidous, S., Msakni,M. and Haouari, M.(2016), Optimal planning of liquefied natural gas deliveries, Transportation Research Part C, Vol. 69, pp. 79 –90
Alvarez, J. F., Tsilingiris, P., Engebrethsen, E., and Kakalis, N. M. P. (2011). Robust flee sizing and deployment for industrial and independent bulk ocean shipping companies. INFOR, Vol. 49(2), pp. 93–107.
Anderson, H., Christiansen, M., and Fagerholt, K. (2010). Transportation planning and inventory management in the LNG supply chain. In Bjørndal, E., Pardolos, P. M., and Ronnqvist, M., editors, Energy, Natural Resources and Environmental Economics. Springer, Berlin.
Andersson, H., Christiansen, M., and Desaulniers, G. (2015a). A new decomposition algorithm for a liquefied natural gas inventory routing problem. International Journal of Production Research, Accepted 29 Jan 2015, Published online: 07 May 2015.
Andersson, H., Christiansen, M., and Desaulniers, G. and Rakke, J., (2015b). Creating annual delivery programs of liquefied naturalgas, Springer Science+Business Media New York, Published online.
Barnhart, C., Laporte, G. (Eds.), Handbook in OR & MS, Vol. 14, 2007 Elsevier.
Chengliang Zhang, George Nemhauser, Joel Soko lexible (2017). Flexible Solutions to Maritime Inventory Routing Problems with Delivery Time Windows, Computers and Operations Research, Vol. 89, pp. 153-162.
Cheng, L. and Duran, M.A. (2004). Logistics for world-wide crude oil transportation using discrete event simulation and optimal control. Comput. Chem. Eng. Vol. 28, pp. 897–911.
Christiansen, M. (1999). Decomposition of a combined inventory and time constrained ship routing problem. Transportation Science, Vol. 33, pp. 3–26.
Christiansen, M. and Fagerholt, K. (2002). Robust ship scheduling with multiple time windows. Naval Res. Logistics, Vol. 49, pp. 611–625
Christiansen, M. and Fagerholt, K. (2009). Maritime inventory routing problems. In Floudas, C. A. and Pardalos, P., editors, Encyclopedia of Optimization, pp. 1947–1955. Springer.
Christiansen, M., Fagerholt, K., Flatberg, T., Haugen, Ø., Kloster, O., and Lund, E. H. (2011). Maritime inventory routing with multiple products: A case study from the cement industry. European Journal of Operational Research, Vol. 208(1), pp. 86–94.
Christiansen, M., Fagerholt, K., Nygreen, B., and Ronen, D. (2013). Ship routing and scheduling in the new millennium. European Journal of Operational Research, Vol. 228(3), pp. 467–483.
Christiansen, M., Fagerholt, K., and Ronen, D. (2004). Ship routing and scheduling: Status and perspectives. Transportation Science, Vol. 38, pp. 1–18.
Coelho, L. C., Cordeau, J.-F., and Laporte, G. (2013). Thirty years of inventory routing. Transportation Science. (In press).
Dung-Ying Lin and Yu-Ting Chang, (2018). Ship routing and freight assignment problem for liner shippiApplication to the Northern Sea Route planning problem, Transportation Research Part E, Vol. 110, pp. 47-70
Popović, D., Bjelić, N. and Radivojević, G., (2011), Simulation Approach to Analyse Deterministic IRP Solution of the Stochastic Fuel Delivery Problem, Procedia Social and Behavioral Sciences, Vol. 20, pp. 273–282
Engineer, F. G., Furman, K. C., Nemhauser, G. L., Savelsbergh, M. W. P., and Song, J. (2012). A branch-price-and-cut algorithm for single product maritime inventory routing. Operations Research, Vol. 60, pp. 106–122.
Ethan Malinowskia, and Mark H. Karwana, José M. Pintob, Lei Sunc, (2018). A mixed-integer programming strategy for liquid helium global, Transportation Research Part E, Vol. 110, pp. 168–188.
Fodstad, M., Uggen, K. T., Rّmo, F., Lium, A., and Stremersch, G. (2010). LNGScheduler: A rich model for coordinating vessel routing, inventories and trade in the liquefied natural gas supply chain. Journal of Energy Markets, Vol. 3(4), pp. 31–64.
Furman, K. C., Song, J.-H., Kocis, G. R., McDonald, M. K., and Warrick, P. H. (2011). Feedstock routing in the exxonmobil downstream sector. Interfaces, Vol. 41(2), pp. 149–163.
Ghiami, Y., Woensel, T., Christiansen, M., and Laporte, G.,(2015), A Combined Liquefied Natural Gas Routing and Deteriorating Inventory Management Problem, Springer International Publishing Switzerland 2015, F. Corman et al. (Eds.): ICCL 2015, LNCS.
Goel, V., Furman, K. C., Song, J.-H., and El-Bakry, A. S. (2012). Large neighborhood search for lng inventory routing. Journal of Heuristics, Vol. 18(6), pp. 821– 848.
Goel, V., Slusky, M., van Hoeve, W.-J., Furman, K., and Shao, Y. (2015). Constraint programming for lng ship scheduling and inventory management. European Journal of Operational Research, Vol. 241(3), pp. 662–673.
Grønhaug, R., Christiansen, M., Desaulniers, G., and Desrosiers, J. (2010). A branch-and-price method for a liquefied natural gas inventory routing problem. Transportation Science, Vol. 44(3), pp. 400–415.
Halvorsen-Weare, E. E. and Fagerholt, K. (2013). Routing and scheduling in a liquefied natural gas shipping problem with inventory and berth constraints. Annals of Operations Research, Vol. 203(1), pp. 167–186.
Halvorsen-Weare, E. E., Fagerholt, K.: Robust supply vessel planning. In: Pahl, J., Reiners, T., Voک, S. (eds.) INOC 2011. LNCS, Vol. 6701, pp. 559–573. Springer, Heidelberg (2011).
Hemmati, A., Hvattum, L., Christiansen, M. and Laporte, G., (2016), An iterative two-phase hybrid matheuristic for a multi-product short sea inventory-routing problem, European Journal of Operational Research, Vol. 252, pp. 775–788.
Hemmati , A., Stålhane, M., Hvattum, L. and  Andersson, H., (2015), An effective heuristic for solving a combined cargo and inventory routing problem in tramp shipping, Computers & Operations Research, Vol. 64, pp. 274-282.
Hewitt, M., Nemhauser, G. L., Savelsbergh, M., and Song, J. (2013). A branch and-price guided search approach to maritime inventory routing. Computers and Operations Research, Vol. 40, pp. 1410–1419.
Hoff, A., Andersson, H., Christiansen, M., Hasle, G., and Lّkketangen, A. (2010).Industrial aspects and literature survey: Combined inventory management and routing. Computers & Operations Research, Vol. 37(9), pp. 1515–1536.
Li, J., Karimi, I., & Srinivasan, R. (2010). Efficient bulk maritime logistics for the supply and delivery of multiple chemicals. Computers & Chemical Engineering, Vol. 34(12), pp. 2118–2128
Meredith J. (1993). Theory building through conceptual methods. International Journal of Operations & Production Management, Vol. 13(5), pp. 3–11.
Mutlu, F., Msakni, M., Yildiz, H., Sonmez, E., Pokhare, S,. A Comprehensive Annual Delivery Program for Upstream Liquefied Natural Gas Supply Chain, Journal of Operational Research, Vol. 250, pp. 120- 130.
Nikhalat-Jahromi, N., Bell, G., Fontes, D., Cochrane, R. and Angeloudis, P,. (2016), Spot sale of uncommitted LNG from Middle East: Japan or the UK?, Energy Policy, Vol. 96, pp. 717–725.
Papageorgiou, D. J., Cheon, M.-S., Nemhauser, G., and Sokol, J. (2014a). Approximate dynamic programming for a class of long-horizon maritime inventory routing problems. Transportation Science. Vol. 49, pp. 850- 885.
Papageorgiou, D. J., Keha, A. B., Nemhauser, G. L., and Sokol, J. (2014b). Two-stage decomposition algorithms for single product maritime inventory routing. INFORMS Journal on Computing, Vol. 26(4), pp. 825–847.
Papageorgiou, D. J., Nemhauser, G. L., Sokol, J., Cheon, M.-S., and Keha, A. B. (2014c). Mirplib–a library of maritime inventory routing problem instances: Survey, core model, and benchmark results. European Journal of Operational Research, Vol. 235(2), pp. 350–366.
Persson, J. A. and Gothe-Lundgren, M. (2005). Shipment planning at oil refineries using column generation and valid inequalities. European Journal of Operational Research, Vol. 163, pp. 631–652.
Rakke, J. G., Andersson, H., Christiansen, M., and Desaulniers, G. (2014). A new formulation based on customer delivery patterns for a maritime inventory routing problem. Transportation Science, Vol. 49(2), pp. 384–401.
Rakke, J. G., Stalhane, M., Moe, C. R., Christiansen, M., Andersson, H., Fagerholt, K., and Norstad, I. (2011). A rolling horizon heuristic for creating a liquefied natural gas annual delivery program. Transportation Research Part C, Vol. 19, pp. 896–911.
Rocha, R., Grossmann, I. E., and de Aragمo, M. V. P. (2013). Cascading knapsack inequalities: reformulation of a crude oil distribution problem. Annals of Operations Research, Vol. 203(1), pp. 1–18.
Ronen, D. et al. (2002). Marine inventory routing: Shipments planning. Journal of the Operational Research Society, Vol. 53(1), pp. 108–114.
Seuring, S. and Muller, M., (2008). From a literature review to a conceptual framework for sustainable supply chain management, Journal of Cleaner Production, Vol. 16, pp. 1699–1710.
Shao, Y., Furman, K. C., Goel, V., and Hoda, S. (2015). A hybrid heuristic strategy for liquefied natural gas inventory routing. Transportation Research Part C: Emerging Technologies, Vol. 53, pp. 151–171.
Shen, Q., Chu, F., and Chen, H. (2011). A Lagrangian relaxation approach for a multimode inventory routing problem with transshipment in crude oil transportation. Computers & Chemical Engineering, Vol. 35(10), pp. 2113–2123.
Shyshou, A., Gribkovskaia, I., & Barcelَ, J. (2010). A simulation study of the fleetsizing problem arising in offshore anchor handling operations. European Journal of Operational Research, Vol. 203(1), pp. 230–240.
Siswanto, N., Essam, D., and Sarker, R. (2011). Multi-heuristics based genetic algorithm for solving maritime inventory routing problem. In Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on, pp. 116–120. IEEE.
St¨alhane, M., Rakke, J. G., Moe, C. R., Andersson, H., Christiansen, M., and Fagerholt, K. (2012). A construction and improvement heuristic for an lng inventory routing problem. Computers & Industrial Engineering, Vol. 62, pp. 245– 255.
Song, J. and Furman, K. C. (2013). A maritime inventory routing problem: Practical approach. Computers and Operations Research, Vol. 40, pp. 657–665.
SteadieSeifi, M.,Dellaert,N.P., Nuijten,W., Woensel, T. and Raoufi, R.,(2014), Multimodal freight transportation planning: A literature review, European Journal of Operational Research, Vol. 233, pp. 1–15.
Uggen, K., Fodstad, M., and Nørstebø, V. (2013). Using and extending fix-and-relax to solve maritime inventory routing problems. TOP, Vol. 21(2), pp. 355–377.
Yongheng, J. and Grossmann, I. E. (2015). Alternative mixed-integer linear programming models of a maritime inventory routing problem. Computers & Chemical Engineering, Vol. 77, pp. 147–161.
European Commission. European transport policy for 2010: time to decide. White Paper. Luxembourg: Office for Official Publications of the European Communities; 2001.
https://ec.europa.eu/transport/themes/strategies/2001_white_paper_en.
UNCTAD (2012). Review of maritime transport. United Nations, New York and Geneva.
International Journal of Supply and Operations Management
Volume 4, Issue 4 - Serial Number 4
November 2017
Pages 341-358

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