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A mixed integer programming model for long term capacity expansion planning: a case study from the Hunter valley coal chain. (English) Zbl 1253.90157
Summary: The Hunter Valley Coal Chain is the largest coal export operation in the world with a throughput in excess of 100 million tonnes per annum (Mtpa). Coal is delivered to the shipping terminal from 40 mines using 27 coal load points spread across the Hunter Valley region. This paper describes an MILP model for determining the capacity requirements, and the most cost effective capacity improvement initiatives, to meet demand while minimising the total cost of infrastructure and demurrage. We present results from computational experiments on the model’s performance along with a comparison of the model’s output with detailed analyses by the coal chain analysts and planners.

90B90 Case-oriented studies in operations research
90C11 Mixed integer programming
90B06 Transportation, logistics and supply chain management
Full Text: DOI
[1] Ahmed, S.; Sahinidis, N., An approximation scheme for stochastic integer programs arising in capacity expansion, Operations research, 51, 461-471, (2003) · Zbl 1163.90677
[2] Aickelin, U.; Burke, E.K.; Li, J., An evolutionary squeaky wheel optimization approach to personnel scheduling, IEEE transactions on evolutionary computation, 13, 433-443, (2009)
[3] Bayer, A.; Rademacher, M.; Rutherford, A., Development and perspectives of the Australian coal supply chain and implications for the export market, Zeitschrift für energiewirtschaft, 33, 255-267, (2009)
[4] Bernardo, J.; Gillenwater, E., Sequencing rules for productivity improvements in underground coal mining, Decision sciences, 22, 620-634, (1991)
[5] Birge, J., Option methods for incorporating risk into linear capacity planning models, Manufacturing & service operations management, 2, 19-31, (2000)
[6] Burdett, R.; Kozan, E., A sequencing approach for creating new train timetables, OR spectrum, 32, 163-193, (2010) · Zbl 1181.90112
[7] Chen, Z.-L.; Hall, N., Supply chain scheduling: conflict and cooperation in assembly systems, Operations research, 55, 1072-1192, (2007) · Zbl 1167.90504
[8] Conradie, D.; Morison, L.; Joubert, J., Scheduling at coal handling facilities using simulated annealing, Mathematical methods of operations research, 68, 277-293, (2008) · Zbl 1279.90063
[9] Dorfman, M.; Medanic, J., Scheduling trains on a railway network using a discrete event model of railway traffic, Transportation research part B, 38, 81-98, (2004)
[10] Fliedner, G., CPFR: an emerging supply chain tool, Industrial management & data syatems, 103, 14-21, (2003)
[11] Grossmann, I., Challenges in the new millennium: product discovery and design, enterprise and supply chain optimization, global life cycle assessment, Computers and chemical engineering, 29, 29-39, (2004)
[12] Guillena, G.; Melea, F.; Bagajewiczb, M.; Espunaa, A.; Puigjanera, L., Multiobjective supply chain design under uncertainty, Chemical engineering science, 60, 1535-1553, (2005)
[13] Gupta, A.; Maranas, C., Managing demand uncertainty in supply chain planning, Computers and chemical engineering, 27, 1219-1227, (2003)
[14] Hall, N.; Potts, C., Supply chain scheduling: batching and delivery, Operations research, 51, 566-584, (2003) · Zbl 1165.90455
[15] Huh, W.; Roundy, R.; Cakanyildirim, M., A general strategic capacity planning model under demand uncertainty, Naval research logistics, 53, 137-150, (2006) · Zbl 1106.90326
[16] Joslin, D.; Clements, D., Squeaky wheel optimization, Journal of artificial intelligence research, 10, 353-373, (1999) · Zbl 0918.90120
[17] Korpela, J.; Kyläheiko, K.; Lehmusvaara, A.; Tuominen, M., An analytic approach to production capacity allocation and supply chain design, International journal of production economics, 78, 187-195, (2002)
[18] Lourenço, H.R.; Martin, O.C.; Stützle, T., Iterated local search, (), 320-353 · Zbl 1116.90412
[19] Meixell, M.; Gargeya, V., Global supply chain design: A literature review and critique, Transportation research part E, 41, 531-550, (2005)
[20] Melo, M.; Nickel, S.; Saldanha-da Gama, F., Dynamic multi-commodity capacitated facility location: A mathematical modeling framework for strategic supply chain planning, Computers & operations research, 33, 181-208, (2005) · Zbl 1077.90006
[21] Melo, M.; Nickel, S.; Saldanha-da Gama, F., Facility location and supply chain management: A review, European journal of operational research, 196, 401-412, (2009) · Zbl 1163.90341
[22] Mukherjee, K., Application of an interactive method for MOILP in project selection decision - A case from Indian coal mining industry, International journal of production economics, 36, 203-211, (1994)
[23] Mukherjee, K.; Bera, A., Application of goal programming in project selection decision - A case study from the Indian coal mining industry, European journal of operational research, 82, 18-25, (1995) · Zbl 0904.90107
[24] Narasimhan, R.; Mahapatra, S., Decision models in global supply chain management, Industrial marketing management, 33, 21-27, (2004)
[25] Newman, A.; Rubio, E.; Caro, R.; Weintraub, A.; Eurek, K., A review of operations research in mine planning, Interfaces, 40, 222-245, (2010)
[26] Park, Y., An integrated approach for production and distribution planning in supply chain management, International journal of production research, 43, 1205-1224, (2005) · Zbl 1068.90557
[27] Pendharkar, P.; Rodger, J., Non-linear programming and genetic search application for production scheduling in coal mines, Annals of operations research, 23, 251-267, (2000) · Zbl 0997.90540
[28] Peng, H.-j.; Zhou, M.-h.; Liu, M.-z.; Zhang, Y.; Huang, Y.-b., A dynamic optimization model of an integrated coal supply chain system and its application, Mining science and technology, 19, 842-846, (2009)
[29] Petersen, K.; Ragatz, G.; Monczka, R., An examination of collaborative planning effectiveness and supply chain performance, Journal of supply chain management, 41, 14-25, (2005)
[30] Port Waratah Coal Services Limited, 2007. COAL TERMINALS INFORMATION HANDBOOK. Revision 4, Effective from June 200. <http://www.pwcs.com.au/pages/about/handbook.php>.
[31] Power, D., Supply chain management integration and implementation: A literature review, Supply chain management: an international journal, 10, 252-263, (2005)
[32] Romano, P., And integration mechanisms to manage logistics processes across supply networks, Journal of purchasing & supply management, 9, 119-134, (2003)
[33] Santoso, T.; Ahmed, S.; Goetschalckx, M.; Shapiro, A., A stochastic programming approach for supply chain network design under uncertainty, European journal of operational research, 167, 96-115, (2005) · Zbl 1075.90010
[34] Stadtler, H., Supply chain management and advanced planning basics, overview and challenges, European journal of operational research, 163, 575-588, (2005) · Zbl 1071.90006
[35] Trkman, P.; McCormack, K.; Valadares de Oliveira, M.; Ladeira, M., The impact of business analytics on supply chain performance, Decision support systems, 49, 318-327, (2010)
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