Home   >   CSC-OpenAccess Library   >    Manuscript Information
A Supply Chain Design Approach to Petroleum Distribution
Avninder Gill
Pages - 33 - 44     |    Revised - 31-03-2011     |    Published - 04-04-2011
Volume - 2   Issue - 1    |    Publication Date - March / April 2011  Table of Contents
MORE INFORMATION
KEYWORDS
Supply Chain, Petroleum Distribution, Mathematical Programming
ABSTRACT
Product distribution account for a significant portion of the logistical costs of a product. Distribution activities are repetitive in nature and they impact the delivery lead time to customers. A well designed supply chain network can substantially improve these costs and lead times. This paper presents a supply chain network design approach for distribution of petroleum products of a retailer by identifying the depot locations and gas station allocations. A heuristic procedure to solve large sized problems is also recommended. Finally, concluding remarks and recommendations for further research are presented.
CITED BY (7)  
1 Gromov, V. A., Kuznietzov, K. A., & Pigden, T. (2019). Decision support system for light petroleum products supply chain. Operational Research, 19(1), 219-236.
2 Moradinasab, N., Jafarzadeh, H., Amin-Naseri, M. R., & Fleming, C. H. (2019). A Dynamic Sustainable Competitive Petroleum Supply Chain Model for Various Stakeholders with Shared Facilities. arXiv preprint arXiv:1907.11789.
3 Aziz, A., & Hussain, I. (2018, June). Design and Optimization of a Multi-echelon Supply Chain Network for Product Distribution with Cross-Route Costs and Traffic Factor Values. In International Conference on Mobile and Wireless Technology (pp. 381-391). Springer, Singapore.
4 Moradinasab, N., Amin-Naseri, M. R., Behbahani, T. J., & Jafarzadeh, H. (2018). Competition and cooperation between supply chains in multi-objective petroleum green supply chain: A game theoretic approach. Journal of cleaner production, 170, 818-841.
5 Nasab, N. M., & Amin-Naseri, M. R. (2016). Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain. Energy, 114, 708-733.
6 Al Hadhrami, A. (2016). Oil & Gas Value Chain and Local Content Role in Aiding Job Creation and Adding Human Resource Value to the Omani Economy (Doctoral dissertation, University of Liverpool).
7 Branski, R. M. (2015). Logística na cadeia do petróleo: uma revisão sistemática. Revista ANPET: Associação Nacional de Pesquisa e Ensino em Transportes, Ouro Preto, MG, 915-927.
1 Google Scholar 
2 CiteSeerX 
3 Scribd 
4 SlideShare 
5 PdfSR 
Ageev, A., Ye, Y. and Zhang, J., (2005), “Improved combinatorial approximation algorithm for the k-level facility location problem”, SIAM Journal of Discrete Mathematics, Vol. 18, pp. 207-217.
Amiri, A. (2004), “Designing a distribution network in a supply chin system: formulation and deficient solution procedure”, European Journal of Operational Research, Vol. 132, pp. 325-358.
Ballou, R.(1999), Business Logistics Management, 4th International Edition, Prentice Hall Inc., New Jersey, 483-500.
Berman,O. and Krass, D.(2001), Facility location problems with stochastic demands and congestion , In Facility Location: Applications & Theory, ed. DREZNER, Z. and HAMACHAR, H.W., New York: Spring-Verlag., pp. 331-373.
Brandeau, M. and Chiu, S. (1989), “An overview of representative problems in location research,” Management Science, Vol. 35, No. 6 , pp. 645-674.
Burkard, R.E. and Dollani, H., (2001), Robust location problems with pos/neg weights on a tree network, tools for better distribution, Networks, Vol. 38, No. 2, pp. 102-113.
Cornuejols, G., Nemhauser, G.L. and Wolsey, L.A. (1990), “ The uncapacitated facility location problem”, in Discreet Location ( R.L. Francis and P.B. Mirchandani eds.), Wiley, Inter-Science, pp. 119-168.
Crainic, T.G., Delorme, L. and Dejax, P.J. (1993), “A branch and bound method for multicommodity location/allocation with balancing requirements”,European Journal of Operational Research, Vol. 65, No. 3, pp. 368-382.
Crainic, T.G., Delorme, L. and Dejax, P.J.(1989), “Models for multimode multi-commodity location problems with inter-depot balancing requirements”, Annals of Operations Research, Vol. 18, pp. 279-302.
Gendreau, M. , Laporte, G. and Semet, F. (1997), “Solving an ambulance location model by tabu search”, Location Science, Vol. 5, No. 2, pp. 75-88.
Gendron, B. and Crainic, T.G. (1997), “A parallel branch and bound method for multicommodity location with balancing requirements”, Computers and Operations Research, Vol. 24, No. 9, pp. 829-847.
Ghosh, D. (2003), “Neighborhood search heuristics for the un-capacitated facility location problem”, European Journal of Operational Research, Vol. 150, pp. 150-162.
Gill, A and Bhatti, M. I. (2007), “An optimal model for warehouse location and retailer allocation”, Applied Stochastic Models in Business & Industry Journal, Vol. 23, pp 213-221.
Hall, A.E. (1988), “Program finds new sites in multi-facility location problem,” Industrial Engineering, May, pp. 71-74.
Han, D., Kwon, I.G., Bae, M. and Sung, H. (2002), “Supply chain integration in developing countries for foreign retailers in Korea: Wal-Mart experience”,Computers and Industrial Engineering, Vol. 43, pp. 111-121.
Ho, P., and Perl, J. (1995), “Warehouse location under service sensitive demand”, Journal of Business Logistics, Vol. 16, No. 1, pp. 133-162.
Ignizio, J.P. and Cavalier, T.M. (1994), Linear Programming , Prentice Hall Inc., New Jersey.
Klose, A. (2000), “A lagrangean relax-and-cut approach for the two stage capacitated facility location problem”, European Journal of Operational Research, Vol. 126, pp. 408-421.
Lee, S. and Luebbe, R. (1987), “The multi-criteria warehouse location problem revisited,” International Journal of Physical Distribution and Materials Management , Vol. 17, No. 3 , pp. 56-59.
Lin, C.K.Y., Chow, C.K. and Chen, A. (2002), “A location, routing, loading problem for bill delivery services”, Computers and Industrial Engineering, Vol. 43, pp. 5-25.
Melo, T.M., Nickel, S. and Gama, D.S.F. (2004),“Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning”, Computers and Operations Research, Vol. 78, pp. 389-400.
Pal, M., Tardos, E. and Wexler, T., (2001), “Facility location with hard capacities”, Proceedings of the 42nd Annual IEEE Symposium on Foundations of Computer Science, 329-338.
Perl, J. and Daskin, M.S. (1984), “A unified warehouse location routing methodology,” Journal of Business Logistics , Vol. 5, No. 1 , pp. 92-111.
Shycon, H. and Maffei, R. (1960), “Simulation tools for better distribution”, Harvard Business Review, Vol. 38, pp. 65-75.
Snyder, L.V., (2003), Supply chain robustness and reliability: models and algorithms, Ph.D. Dissertation, Northwestern University, Dept. of Industrial Engineering and Management Sciences.
Swamy, C. and Kumar, A., (2004), “Primal-dual algorithm for connected facility location problems”, Algorithmica, 40, 245-269.
Syarif, A., Yun, S.Y. and Gen, M. (2002) “Study on multi-stage logistic chain network: a spanning tree based genetic algorithm approach”, Computers and Industrial Engineering, Vol. 43, pp. 299-314.
Zhou, G., Min, H. and Gen, M. (2002) “The balanced allocation of retailers to multiple distribution centers in the supply chain network: a genetic algorithm approach ”, Computers and Industrial Engineering, Vol. 43, pp. 251-261.
Dr. Avninder Gill
Thompson Rivers University - Canada
agill@tru.ca