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A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

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  • da Silva, Aneirson Francisco
  • Marins, Fernando Augusto Silva

Abstract

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution.

Suggested Citation

  • da Silva, Aneirson Francisco & Marins, Fernando Augusto Silva, 2014. "A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill," Energy Economics, Elsevier, vol. 45(C), pages 196-204.
    • Handle: RePEc:eee:eneeco:v:45:y:2014:i:c:p:196-204
    DOI: 10.1016/j.eneco.2014.07.005
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Rafael Paiva & Reinaldo Morabito, 2009. "An optimization model for the aggregate production planning of a Brazilian sugar and ethanol milling company," Annals of Operations Research, Springer, vol. 169(1), pages 117-130, July.
    3. Flavell, RB, 1976. "A new goal programming formulation," Omega, Elsevier, vol. 4(6), pages 731-732.
    4. Yaghoobi, M.A. & Tamiz, M., 2007. "A method for solving fuzzy goal programming problems based on MINMAX approach," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1580-1590, March.
    5. Chang, Ching-Ter, 2007. "Multi-choice goal programming," Omega, Elsevier, vol. 35(4), pages 389-396, August.
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    Cited by:

    1. Yu, L. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2018. "A copula-based flexible-stochastic programming method for planning regional energy system under multiple uncertainties: A case study of the urban agglomeration of Beijing and Tianjin," Applied Energy, Elsevier, vol. 210(C), pages 60-74.
    2. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    3. Junqueira, Rogerio de Ávila Ribeiro & Morabito, Reinaldo, 2019. "Modeling and solving a sugarcane harvest front scheduling problem," International Journal of Production Economics, Elsevier, vol. 213(C), pages 150-160.
    4. Dmitry I. Ignatov & Sergey I. Nikolenko & Taimuraz Abaev & Jonas Poelmans, 2014. "Improving Quality Of Service For Radio Station Hosting: An Online Recommender System Based On Information Fusion," HSE Working papers WP BRP 31/MAN/2014, National Research University Higher School of Economics.
    5. Thadeu Gasparetto & Carlos Fernandez-Jardon & Angel Barajas, 2014. "Brand Teams And Distribution Of Wealth In Brazilian State Championships," HSE Working papers WP BRP 30/MAN/2014, National Research University Higher School of Economics.
    6. Donya Rahmani & Arash Zandi & Sara Behdad & Arezou Entezaminia, 2021. "A light robust model for aggregate production planning with consideration of environmental impacts of machines," Operational Research, Springer, vol. 21(1), pages 273-297, March.

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    More about this item

    Keywords

    Aggregate production planning; Goal Programming; Fuzzy Goal Programming; Sugar and ethanol mills;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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