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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
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    References listed on IDEAS

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    1. 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.
    2. William H. Taubert, 1968. "A Search Decision Rule for the Aggregate Scheduling Problem," Management Science, INFORMS, vol. 14(6), pages 343-359, February.
    3. 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.
    4. 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.
    5. 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.
    6. Buxey, Geoff, 1988. "Production planning under seasonal demand: A case study perspective," Omega, Elsevier, vol. 16(5), pages 447-455.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    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. 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.
    14. 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.
    15. 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.
    16. Buxey, Geoff, 2003. "Strategy not tactics drives aggregate planning," International Journal of Production Economics, Elsevier, vol. 85(3), pages 331-346, September.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
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    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.

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