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Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company

DECISION volume 45, pages 207–224 (2018)Cite this article

Abstract

In this paper, an application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired thermal power-generating company is presented. Results show that there is immense potential not only for significant cost savings but also for reduced logistics between different coal source–power plant pairs. The target plant load factor at each power plant can be achieved without the need of any imported coal which would not only save precious foreign exchange, but also reduce the logistics involved in the import of coal and transport to power plants. Sensitivity analyses have also been performed with varying coal supply and coal quality levels. The issue of greenhouse gas (GHG) emissions from coal-fired power plants has also been addressed. The trade-off between the optimal total cost and GHG emission targets has been explored. Results show that it is possible to significantly reduce carbon footprints with a marginal increase in the optimal total cost and without the need of import of coal. However, if it is desired to further reduce GHG emission targets, optimal total costs rise substantially with imported coal gradually substituting domestic coal. It is believed that the results presented in this paper would provide a fresh perspective with regard to the allocation and movement of coal. Finally, recommendations and concluding remarks are presented.

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Notes

  1. The name of the company has been suppressed to maintain confidentiality.

  2. USD 1 ~ Rs. 63.87 as on September 9, 2017.

  3. The number and locations of the power plants have been suppressed to maintain confidentiality.

  4. The number and locations of the coal sources (mines) have been suppressed to maintain confidentiality.

  5. The years have been suppressed to maintain confidentiality. However, it may be noted that they are in the current decade.

  6. Raw data provided by the Company have not been presented in the paper to maintain confidentiality.

  7. Boiler capacity is defined in terms of the coal input rate. Ideally, the coal input rate should be within the design capacity of the boiler. However, if the coal input rate is higher than the boiler design capacity for some reason, it must be within the worst capacity of the boiler.

References

  • Amaya CA, Carvajal J, Castaño F (2013) A heuristic framework based on linear programming to solve the constrained joint replenishment problem (C-JRP). Int J Prod Econ 144(1):243–247

    Article  Google Scholar 

  • Arriaga H, Viguria M, López DM, Merino P (2017) Ammonia and greenhouse gases losses from mechanically turned cattle manure windrows: a regional composting network. J Environ Manage 203(1):557–563

    Article  Google Scholar 

  • Bento CB, Filoso S, Pitombo LM, Cantarella H, Rossetto R, Martinelli LA, do Carmo JB (2018) Impacts of sugarcane agriculture expansion over low-intensity cattle ranch pasture in Brazil on greenhouse gases. J Environ Manage 206:980–988

    Article  Google Scholar 

  • Bentz C, Cornaz D, Ries B (2013) Packing and covering with linear programming: a survey. Eur J Oper Res 227(3):409–422

    Article  Google Scholar 

  • Borgonovo E, Buzzard GT, Wendell RE (2018) A global tolerance approach to sensitivity analysis in linear programming. Eur J Oper Res 267(1):321–337

    Article  Google Scholar 

  • Capitanescu F, Marvuglia A, Benetto E, Ahmadi A, Tiruta-Barna L (2017) Linear programming-based directed local search for expensive multi-objective optimization problems: application to drinking water production plants. Eur J Oper Res 262(1):322–334

    Article  Google Scholar 

  • Chandra A, Chandra H (2004) Impact of Indian and imported coal on indian thermal power plants. J Sci Ind Res 63:156–162

    Google Scholar 

  • Charkhgard H, Savelsbergh M, Talebian M (2018) A linear programming based algorithm to solve a class of optimization problems with a multi-linear objective function and affine constraints. Comput Oper Res 89:17–30

    Article  Google Scholar 

  • Choobineh FF, Asef-Vaziri A, Huang X (2012) fleet sizing of automated guided vehicles: a linear programming approach based on closed queuing networks. Int J Prod Res 50(12):3222–3235

    Article  Google Scholar 

  • Daham H, Yang X, Warnes M (2017) An efficient mixed integer programming model for pairing containers in inland transportation based on the assignment of orders. J Oper Res Soc 68(6):678–694

    Article  Google Scholar 

  • de Almeida PN, Dias LC (2012) Value-based DEA models: application-driven developments. J Oper Res Soc 63(1):16–27

    Article  Google Scholar 

  • Dountio EG, Meukam P, Tchaptchet DLP, Ango LEO, Simo A (2016) Electricity generation technology options under the greenhouse gases mitigation scenario: case study of Cameroon. Energy Strategy Reviews 13–14:191–211

    Article  Google Scholar 

  • Falsini D, Fondi F, Schiraldi MM (2012) A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration. Int J Prod Res 50(17):4822–4829

    Article  Google Scholar 

  • Färe R, Grosskopf S, Karagiannis G, Margaritis D (2017) Data envelopment analysis and its related linear programming models. Ann Oper Res 250(1):37–43

    Article  Google Scholar 

  • García J, Florez JE, Torralba Á, Borrajo D, López CL, García-Olaya Á, Sáenz J (2013) Combining linear programming and automated planning to solve intermodal transportation problems. Eur J Oper Res 227(1):216–226

    Article  Google Scholar 

  • Gendron B, Hanafi S, Todosijević R (2018) Metaheuristics based on iterative linear programming and slope scaling for multicommodity fixed charge network design. Eur J Oper Res. https://doi.org/10.1016/j.ejor.2018.01.022

    Article  Google Scholar 

  • Ghaderi M, Ruiz F, Agell N (2017) A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding. Eur J Oper Res 259(3):1073–1084

    Article  Google Scholar 

  • Ghodke S, Kumar R, Singh N, Khandelwal H (2012) Estimation of greenhouse gas emission from indian coal based thermal power plants. IOSR Journal of Engineering 2(4):591–597

    Article  Google Scholar 

  • Govindan K, Sivakumar R (2016) Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Ann Oper Res 238(1/2):243–276

    Article  Google Scholar 

  • Henderson B, Golub A, Pambudi D, Hertel T, Godde C, Herrero M, Cacho O, Gerber P (2018) The power and pain of market-based carbon policies: a global application to greenhouse gases from ruminant livestock production. Mitig Adapt Strat Glob Change 23(3):349–369

    Article  Google Scholar 

  • Hwang K-L, Choi S-M, Kim M-K, Heo J-B, Zoh K-D (2017) Emission of greenhouse gases from waste incineration in Korea. J Environ Manage 196:710–718

    Article  Google Scholar 

  • Kim D-G, Kirschbaum MUF (2015) The effect of land-use change on the net exchange rates of greenhouse gases: a compilation of estimates. Agr Ecosyst Environ 208:114–126

    Article  Google Scholar 

  • Koçyiğit Ç, Bayrak H, Pınar M (2018) Robust auction design under multiple priors by linear and integer programming. Ann Oper Res 260(1/2):233–253

    Article  Google Scholar 

  • Kulturel-Konak S, Konak A (2013) Linear programming based genetic algorithm for the unequal area facility layout problem. Int J Prod Res 51(3):4302–4324

    Article  Google Scholar 

  • La Notte A, Tonin S, Lucaroni G (2018) Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory. Environ Impact Assess Rev 69:82–93

    Article  Google Scholar 

  • Luathep P, Sumalee A, Lam WHK, Li Z-C, Lo HK (2011) Global optimization method for mixed transportation network design problem: a mixed-integer linear programming approach. Transportation Research Part B: Methodological 45(5):808–827

    Article  Google Scholar 

  • Mansini R, Ogryczak W, Speranza MG (2014) Twenty years of linear programming based portfolio optimization. Eur J Oper Res 234(2):518–535

    Article  Google Scholar 

  • Mantoam EJ, Romanelli TL, Gimenez LM (2016) Energy demand and greenhouse gases emissions in the life cycle of tractors. Biosys Eng 151:158–170

    Article  Google Scholar 

  • Massé P, Gibrat R (1957) Application of linear programming to investments in the electric power industry. Manage Sci 3(2):149–166

    Article  Google Scholar 

  • Ministry of Environment and Forests, Government of India (2010) India: Greenhouse Gas Emissions 2007. http://www.moef.nic.in/downloads/public-information/Report_INCCA.pdf, Accessed 9 September, 2017

  • Mittal, M.L., Sharma, C. and Singh, R. (2012) Estimates of Emissions from Coal Fired Thermal Power Plants in India. Available at https://www3.epa.gov/ttnchie1/conference/ei20/session5/mmittal.pdf. Accessed 9 September, 2017

  • Molina F, Morabito R, de Araujo SA (2016) MIP models for production lot sizing problems with distribution costs and cargo arrangement. J Oper Res Soc 67(11):1395–1407

    Article  Google Scholar 

  • Nazari A, Thiruvady D, Aleti A, Moser I (2016) A mixed integer linear programming model for reliability optimization in the component deployment problem. J Oper Res Soc 67(8):1050–1060

    Article  Google Scholar 

  • Niu H, Zhao X, Gao R (2015) train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: nonlinear integer programming models with linear constraints. Transportation Research Part B: Methodological 76:117–135

    Article  Google Scholar 

  • Ozceylan E, Paksoy T (2013) Fuzzy multi-objective linear programming approach for optimizing a closed-loop supply chain network. Int J Prod Res 51(8):2443–2461

    Article  Google Scholar 

  • Pradhan BB, Shrestha RM, Hoa NT, Matsuoka Y (2017) Carbon prices and greenhouse gases abatement from agriculture, forestry and land use in Nepal. Glob Environ Change 43:26–36

    Article  Google Scholar 

  • Tan RR, Aviso KB, Cayamanda CD, Chiu ASF, Promentilla MAB, Ubando AT, Yu KDS (2016) A fuzzy linear programming enterprise input–output model for optimal crisis operations in industrial complexes. Int J Prod Econ 181(Part B):410–418

    Article  Google Scholar 

  • Tempelmeier H, Hilger T (2015) Linear programming models for a stochastic dynamic capacitated lot sizing problem. Comput Oper Res 59:119–125

    Article  Google Scholar 

  • Tempelmeier H, Hilger T (2018) Corrigendum: linear programming models for a stochastic dynamic capacitated lot sizing problem. Comput Oper Res 91:258–259

    Article  Google Scholar 

  • Temple J (2018) Sending heat into space: skycool’s advanced materials could reinvent air conditioning and refrigeration-cutting costs and greenhouse gases in the process. MIT Technology Review 121(1):84–91

    Google Scholar 

  • Umetani S, Fukushima Y, Morita H (2017) A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system. Omega 67:115–122

    Article  Google Scholar 

  • van Pelt TD, Fransoo JC (2018) A note on linear programming models for a stochastic dynamic capacitated lot sizing problem. Comput Oper Res 89:13–16

    Article  Google Scholar 

  • Wang H-F, Zheng K-W (2013) Application of fuzzy linear programming to aggregate production plan of a refinery industry in Taiwan. J Oper Res Soc 64(2):169–184

    Article  Google Scholar 

  • Wang EJ, Chen YC, Wang WS, Su TS (2010) Analysis of outsourcing cost-effectiveness using a linear programming model with fuzzy multiple goals. Int J Prod Res 48(2):501–523

    Article  Google Scholar 

  • Wu Y, Zhang L (2017) Can the development of electric vehicles reduce the emission of air pollutants and greenhouse gases in developing countries? Transp Res Part D 51:129–145

    Article  Google Scholar 

  • Yang L, Zhou X (2017) Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks. Transportation Research Part B: Methodological 96:68–91

    Article  Google Scholar 

  • Yin J, Yang L, Tang T, Gao Z, Ran B (2017) Dynamic passenger demand oriented metro train scheduling with energy efficiency and waiting time minimization: mixed-integer linear programming approaches. Transportation Research Part B: Methodological 97:182–213

    Article  Google Scholar 

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Acknowledgements

The authors are thankful to the Company for entrusting with the project and providing all the necessary data and information for this purpose.

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Authors and Affiliations

  1. Indian Institute of Management Calcutta, Diamond Harbour Road, Joka, Kolkata, 700104, India

    Subrata Mitra & Balram Avittathur

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  1. Subrata Mitra
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  2. Balram Avittathur
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Correspondence to Subrata Mitra.

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Mitra, S., Avittathur, B. Application of linear programming in optimizing the procurement and movement of coal for an Indian coal-fired power-generating company. Decision 45, 207–224 (2018). https://doi.org/10.1007/s40622-018-0184-x

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