IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v7y2015i12p15819-16339d60355.html
   My bibliography  Save this article

Optimal Control Approaches to the Aggregate Production Planning Problem

Author

Listed:
  • Yasser A. Davizón

    (Unidad Académica de Ingeniería Mecatrónica, Universidad Politécnica de Sinaloa, 82199 Mazatlán, Mexico)

  • César Martínez-Olvera

    (Industrial Engineering Department, Tecnológico de Monterrey, Campus Aguascalientes, 20328 Aguascalientes, Mexico)

  • Rogelio Soto

    (School of Sciences and Engineering, Tecnológico de Monterrey, Campus Monterrey, 64849 Monterrey, Mexico)

  • Carlos Hinojosa

    (School of Sciences and Engineering, Tecnológico de Monterrey, Campus Monterrey, 64849 Monterrey, Mexico)

  • Piero Espino-Román

    (Unidad Académica de Ingeniería Mecatrónica, Universidad Politécnica de Sinaloa, 82199 Mazatlán, Mexico)

Abstract

In the area of production planning and control, the aggregate production planning (APP) problem represents a great challenge for decision makers in production-inventory systems. Tradeoff between inventory-capacity is known as the APP problem. To address it, static and dynamic models have been proposed, which in general have several shortcomings. It is the premise of this paper that the main drawback of these proposals is, that they do not take into account the dynamic nature of the APP. For this reason, we propose the use of an Optimal Control (OC) formulation via the approach of energy-based and Hamiltonian-present value. The main contribution of this paper is the mathematical model which integrates a second order dynamical system coupled with a first order system, incorporating production rate, inventory level, and capacity as well with the associated cost by work force in the same formulation. Also, a novel result in relation with the Hamiltonian-present value in the OC formulation is that it reduces the inventory level compared with the pure energy based approach for APP. A set of simulations are provided which verifies the theoretical contribution of this work.

Suggested Citation

  • Yasser A. Davizón & César Martínez-Olvera & Rogelio Soto & Carlos Hinojosa & Piero Espino-Román, 2015. "Optimal Control Approaches to the Aggregate Production Planning Problem," Sustainability, MDPI, vol. 7(12), pages 1-16, December.
  • Handle: RePEc:gam:jsusta:v:7:y:2015:i:12:p:15819-16339:d:60355
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/7/12/15819/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/7/12/15819/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Reay-Chen & Liang, Tien-Fu, 2005. "Applying possibilistic linear programming to aggregate production planning," International Journal of Production Economics, Elsevier, vol. 98(3), pages 328-341, December.
    2. Chandra, Charu & Grabis, Janis, 2005. "Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand," European Journal of Operational Research, Elsevier, vol. 166(2), pages 337-350, October.
    3. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2003. "Measuring and avoiding the bullwhip effect: A control theoretic approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 567-590, June.
    4. Gansterer, Margaretha, 2015. "Aggregate planning and forecasting in make-to-order production systems," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 521-528.
    5. Disney, S. M. & Naim, M. M. & Towill, D. R., 2000. "Genetic algorithm optimisation of a class of inventory control systems," International Journal of Production Economics, Elsevier, vol. 68(3), pages 259-278, December.
    6. Gomes da Silva, Carlos & Figueira, José & Lisboa, João & Barman, Samir, 2006. "An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming," Omega, Elsevier, vol. 34(2), pages 167-177, April.
    7. Buxey, Geoff, 1988. "Production planning under seasonal demand: A case study perspective," Omega, Elsevier, vol. 16(5), pages 447-455.
    8. Poles, Roberto, 2013. "System Dynamics modelling of a production and inventory system for remanufacturing to evaluate system improvement strategies," International Journal of Production Economics, Elsevier, vol. 144(1), pages 189-199.
    9. Kim, Bokang & Kim, Sooyoung, 2001. "Extended model for a hybrid production planning approach," International Journal of Production Economics, Elsevier, vol. 73(2), pages 165-173, September.
    10. Naim, M.M. & Wikner, J. & Grubbström, R.W., 2007. "A net present value assessment of make-to-order and make-to-stock manufacturing systems," Omega, Elsevier, vol. 35(5), pages 524-532, October.
    11. D.R. Zanwar & V.S. Deshpande & J.P. Modak & M.M. Gupta & K.N. Agrawal, 2015. "Determination of mass, damping coefficient, and stiffness of production system using convolution integral," International Journal of Production Research, Taylor & Francis Journals, vol. 53(14), pages 4351-4362, July.
    12. Tadei, R. & Trubian, M. & Avendano, J. L. & Della Croce, F. & Menga, G., 1995. "Aggregate planning and scheduling in the food industry: A case study," European Journal of Operational Research, Elsevier, vol. 87(3), pages 564-573, December.
    13. Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2004. "The impact of information enrichment on the Bullwhip effect in supply chains: A control engineering perspective," European Journal of Operational Research, Elsevier, vol. 153(3), pages 727-750, March.
    14. Warburton, Roger D.H. & Hodgson, J.P.E. & Nielsen, E.H., 2014. "Exact solutions to the supply chain equations for arbitrary, time-dependent demands," International Journal of Production Economics, Elsevier, vol. 151(C), pages 195-205.
    15. Agrawal, Sunil & Sengupta, Raghu Nandan & Shanker, Kripa, 2009. "Impact of information sharing and lead time on bullwhip effect and on-hand inventory," European Journal of Operational Research, Elsevier, vol. 192(2), pages 576-593, January.
    16. Das, Sanchoy K. & Sarin, Subhash C., 1994. "An integrated approach to solving the master aggregate scheduling problem," International Journal of Production Economics, Elsevier, vol. 34(2), pages 167-178, March.
    17. William H. Taubert, 1968. "A Search Decision Rule for the Aggregate Scheduling Problem," Management Science, INFORMS, vol. 14(6), pages 343-359, February.
    18. Mula, J. & Poler, R. & Garcia-Sabater, J.P. & Lario, F.C., 2006. "Models for production planning under uncertainty: A review," International Journal of Production Economics, Elsevier, vol. 103(1), pages 271-285, September.
    19. Wang, Reay-Chen & Fang, Hsiao-Hua, 2001. "Aggregate production planning with multiple objectives in a fuzzy environment," European Journal of Operational Research, Elsevier, vol. 133(3), pages 521-536, September.
    20. Buxey, Geoff, 2003. "Strategy not tactics drives aggregate planning," International Journal of Production Economics, Elsevier, vol. 85(3), pages 331-346, September.
    21. Mirzapour Al-e-hashem, S.M.J. & Malekly, H. & Aryanezhad, M.B., 2011. "A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty," International Journal of Production Economics, Elsevier, vol. 134(1), pages 28-42, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Toly Chen, 2016. "Competitive and Sustainable Manufacturing in the Age of Globalization," Sustainability, MDPI, vol. 9(1), pages 1-5, December.
    2. Chia-Nan Wang & Nhat-Luong Nhieu & Trang Thi Thu Tran, 2021. "Stochastic Chebyshev Goal Programming Mixed Integer Linear Model for Sustainable Global Production Planning," Mathematics, MDPI, vol. 9(5), pages 1-22, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, J. & Naim, M.M. & Purvis, L. & Gosling, J., 2017. "The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015," International Journal of Production Economics, Elsevier, vol. 194(C), pages 135-152.
    2. Shih-Pin Chen & Wen-Lung Huang, 2014. "Solving Fuzzy Multiproduct Aggregate Production Planning Problems Based on Extension Principle," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2014, pages 1-18, August.
    3. Andrea Borenich & Peter Greistorfer & Marc Reimann, 2020. "Model-based production cost estimation to support bid processes: an automotive case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 841-868, September.
    4. Ciancimino, Elena & Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2012. "On the Bullwhip Avoidance Phase: The Synchronised Supply Chain," European Journal of Operational Research, Elsevier, vol. 221(1), pages 49-63.
    5. Chatfield, Dean C. & Pritchard, Alan M., 2013. "Returns and the bullwhip effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 159-175.
    6. Sodhi, ManMohan S. & Tang, Christopher S., 2011. "The incremental bullwhip effect of operational deviations in an arborescent supply chain with requirements planning," European Journal of Operational Research, Elsevier, vol. 215(2), pages 374-382, December.
    7. Babai, M.Z. & Boylan, J.E. & Syntetos, A.A. & Ali, M.M., 2016. "Reduction of the value of information sharing as demand becomes strongly auto-correlated," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 130-135.
    8. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
    9. Sagawa, Juliana Keiko & Nagano, Marcelo Seido, 2015. "Modeling the dynamics of a multi-product manufacturing system: A real case application," European Journal of Operational Research, Elsevier, vol. 244(2), pages 624-636.
    10. Aggelogiannaki, Eleni & Sarimveis, Haralambos, 2008. "Design of a novel adaptive inventory control system based on the online identification of lead time," International Journal of Production Economics, Elsevier, vol. 114(2), pages 781-792, August.
    11. Rupesh Kumar Pati, 2014. "Modelling Bullwhip Effect in a Closed Loop Supply Chain with ARMA Demand," IIM Kozhikode Society & Management Review, , vol. 3(2), pages 149-164, July.
    12. Ahmed Shaban & Mohamed A. Shalaby & Giulio Di Gravio & Riccardo Patriarca, 2020. "Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand," Sustainability, MDPI, vol. 12(16), pages 1-27, August.
    13. Wang, Xun & Disney, Stephen M., 2016. "The bullwhip effect: Progress, trends and directions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 691-701.
    14. Mula, Josefa & Peidro, David & Poler, Raul, 2010. "The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand," International Journal of Production Economics, Elsevier, vol. 128(1), pages 136-143, November.
    15. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    16. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio & Boylan, John E., 2020. "The impact of demand parameter uncertainty on the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 283(1), pages 94-107.
    17. Cannella, Salvatore & Framinan, Jose M. & Bruccoleri, Manfredi & Barbosa-Póvoa, Ana Paula & Relvas, Susana, 2015. "The effect of Inventory Record Inaccuracy in Information Exchange Supply Chains," European Journal of Operational Research, Elsevier, vol. 243(1), pages 120-129.
    18. K. Devika & A. Jafarian & A. Hassanzadeh & R. Khodaverdi, 2016. "Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics," Annals of Operations Research, Springer, vol. 242(2), pages 457-487, July.
    19. Wang, Reay-Chen & Liang, Tien-Fu, 2005. "Applying possibilistic linear programming to aggregate production planning," International Journal of Production Economics, Elsevier, vol. 98(3), pages 328-341, December.
    20. Wang, Zhaodong & Wang, Xin & Ouyang, Yanfeng, 2015. "Bounded growth of the bullwhip effect under a class of nonlinear ordering policies," European Journal of Operational Research, Elsevier, vol. 247(1), pages 72-82.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:7:y:2015:i:12:p:15819-16339:d:60355. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.