IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v267y2018i1d10.1007_s10479-017-2568-2.html
   My bibliography  Save this article

A multiple objective methodology for sugarcane harvest management with varying maturation periods

Author

Listed:
  • Helenice de Oliveira Florentino

    (UNESP - Univ Estadual Paulista)

  • Chandra Irawan

    (University of Portsmouth)

  • Angelo Filho Aliano

    (Federal Technology University of Paraná)

  • Dylan F. Jones

    (University of Portsmouth)

  • Daniela Renata Cantane

    (UNESP - Univ Estadual Paulista)

  • Jonis Jecks Nervis

    (UNESP - Univ Estadual Paulista)

Abstract

This paper addresses the management of a sugarcane harvest over a multi-year planning period. A methodology to assist the harvest planning of the sugarcane is proposed in order to improve the production of POL (a measure of the amount of sucrose contained in a sugar solution) and the quality of the raw material, considering the constraints imposed by the mill such as the demand per period. An extended goal programming model is proposed for optimizing the harvest plan of the sugarcane so the harvesting point is as close as possible to the ideal, considering the constrained nature of the problem. A genetic algorithm (GA) is developed to tackle the problem in order to solve realistically large problems within an appropriate computational time. A comparative analysis between the GA and an exact method for small instances is also given in order to validate the performance of the developed model and methods. Computational results for medium and large farm instances using GA are also presented in order to demonstrate the capability of the developed method. The computational results illustrate the trade-off between satisfying the conflicting goals of harvesting as closely as possible to the ideal and making optimum use of harvesting equipment with a minimum of movement between farms. They also demonstrate that, whilst harvesting plans for small scale farms can be generated by the exact method, a meta-heuristic GA method is currently required in order to devise plans for medium and large farms.

Suggested Citation

  • Helenice de Oliveira Florentino & Chandra Irawan & Angelo Filho Aliano & Dylan F. Jones & Daniela Renata Cantane & Jonis Jecks Nervis, 2018. "A multiple objective methodology for sugarcane harvest management with varying maturation periods," Annals of Operations Research, Springer, vol. 267(1), pages 153-177, August.
  • Handle: RePEc:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2568-2
    DOI: 10.1007/s10479-017-2568-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-017-2568-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-017-2568-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Isabel Martins & Mujing Ye & Miguel Constantino & Maria Conceição Fonseca & Jorge Cadima, 2014. "Modeling target volume flows in forest harvest scheduling subject to maximum area restrictions," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 343-362, April.
    2. Bagdon, Benjamin A. & Huang, Ching-Hsun & Dewhurst, Stephen, 2016. "Managing for ecosystem services in northern Arizona ponderosa pine forests using a novel simulation-to-optimization methodology," Ecological Modelling, Elsevier, vol. 324(C), pages 11-27.
    3. Vanja Calija & Andrew Higgins & Phillip Jackson & Leone Bielig & Danny Coomans, 2001. "An Operations Research Approach to the Problem of the Sugarcane Selection," Annals of Operations Research, Springer, vol. 108(1), pages 123-142, November.
    4. Sylva, John & Crema, Alejandro, 2007. "A method for finding well-dispersed subsets of non-dominated vectors for multiple objective mixed integer linear programs," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1011-1027, August.
    5. Demirci, Mehmet & Bettinger, Pete, 2015. "Using mixed integer multi-objective goal programming for stand tending block designation: A case study from Turkey," Forest Policy and Economics, Elsevier, vol. 55(C), pages 28-36.
    6. T. Gómez & M. Hernández & J. Molina & M. León & E. Aldana & R. Caballero, 2011. "A multiobjective model for forest planning with adjacency constraints," Annals of Operations Research, Springer, vol. 190(1), pages 75-92, October.
    7. Dylan Jones & Mehrdad Tamiz, 2010. "Practical Goal Programming," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-5771-9, September.
    8. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
    9. Romero, Carlos, 2004. "A general structure of achievement function for a goal programming model," European Journal of Operational Research, Elsevier, vol. 153(3), pages 675-686, March.
    10. Andrew Higgins & Steve Postma, 2004. "Australian Sugar Mills Optimise Siding Rosters to Increase Profitability," Annals of Operations Research, Springer, vol. 128(1), pages 235-249, April.
    11. Sylva, John & Crema, Alejandro, 2004. "A method for finding the set of non-dominated vectors for multiple objective integer linear programs," European Journal of Operational Research, Elsevier, vol. 158(1), pages 46-55, October.
    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. Angelo Aliano Filho & Helenice Oliveira Florentino & Margarida Vaz Pato & Sônia Cristina Poltroniere & João Fernando Silva Costa, 2022. "Exact and heuristic methods to solve a bi-objective problem of sustainable cultivation," Annals of Operations Research, Springer, vol. 314(2), pages 347-376, July.
    2. Hocine, Amin & Zhuang, Zheng-Yun & Kouaissah, Noureddine & Li, Der-Chiang, 2020. "Weighted-additive fuzzy multi-choice goal programming (WA-FMCGP) for supporting renewable energy site selection decisions," European Journal of Operational Research, Elsevier, vol. 285(2), pages 642-654.
    3. Amalia Utamima & Torsten Reiners & Amir H. Ansaripoor, 2022. "Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields," Annals of Operations Research, Springer, vol. 316(2), pages 955-977, September.
    4. 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.
    5. Aliano Filho, Angelo & A. Oliveira, Washington & Melo, Teresa, 2023. "Multi-objective optimization for integrated sugarcane cultivation and harvesting planning," European Journal of Operational Research, Elsevier, vol. 309(1), pages 330-344.

    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. Tom Rihm & Philipp Baumann, 2018. "Staff assignment with lexicographically ordered acceptance levels," Journal of Scheduling, Springer, vol. 21(2), pages 167-189, April.
    2. Rong, Aiying & Figueira, José Rui, 2013. "A reduction dynamic programming algorithm for the bi-objective integer knapsack problem," European Journal of Operational Research, Elsevier, vol. 231(2), pages 299-313.
    3. Marta Ezquerro & Marta Pardos & Luis Diaz-Balteiro, 2019. "Sustainability in Forest Management Revisited Using Multi-Criteria Decision-Making Techniques," Sustainability, MDPI, vol. 11(13), pages 1-24, July.
    4. Rong, Aiying & Figueira, José Rui, 2014. "Dynamic programming algorithms for the bi-objective integer knapsack problem," European Journal of Operational Research, Elsevier, vol. 236(1), pages 85-99.
    5. Amelia Bilbao-Terol & Mariano Jiménez & Mar Arenas-Parra, 2016. "A group decision making model based on goal programming with fuzzy hierarchy: an application to regional forest planning," Annals of Operations Research, Springer, vol. 245(1), pages 137-162, October.
    6. Ramos, Francisco López & Batres, Rafael & De-la-Cruz-Márquez, Cynthia Griselle & Anzures, Melina López, 2023. "Optimization models for nopal crop planning with land usage expansion and government subsidy," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    7. Lacour, Renaud, 2014. "Approches de résolution exacte et approchée en optimisation combinatoire multi-objectif, application au problème de l'arbre couvrant de poids minimal," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/14806 edited by Vanderpooten, Daniel.
    8. Jones, Dylan & Jimenez, Mariano, 2013. "Incorporating additional meta-objectives into the extended lexicographic goal programming framework," European Journal of Operational Research, Elsevier, vol. 227(2), pages 343-349.
    9. Zgajnar, Jaka & Kavcic, Stane, 2011. "Weighted Goal Programming and Penalty Functions: Whole-farm Planning Approach Under Risk," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 118033, European Association of Agricultural Economists.
    10. Mesquita-Cunha, Mariana & Figueira, José Rui & Barbosa-Póvoa, Ana Paula, 2023. "New ϵ−constraint methods for multi-objective integer linear programming: A Pareto front representation approach," European Journal of Operational Research, Elsevier, vol. 306(1), pages 286-307.
    11. González-Pachón, Jacinto & Romero, Carlos, 2016. "Bentham, Marx and Rawls ethical principles: In search for a compromise," Omega, Elsevier, vol. 62(C), pages 47-51.
    12. Hernandez, M. & Gómez, T. & Molina, J. & León, M.A. & Caballero, R., 2014. "Efficiency in forest management: A multiobjective harvest scheduling model," Journal of Forest Economics, Elsevier, vol. 20(3), pages 236-251.
    13. S. Razavyan, 2016. "A Method for Generating a Well-Distributed Pareto Set in Multiple Objective Mixed Integer Linear Programs Based on the Decision Maker’s Initial Aspiration Level," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(04), pages 1-23, August.
    14. Hocine, Amine, 2018. "Meta goal programing approach for solving multi-criteria de Novo programing problemAuthor-Name: Zhuang, Zheng-Yun," European Journal of Operational Research, Elsevier, vol. 265(1), pages 228-238.
    15. Dylan F. Jones & Graham Wall, 2016. "An extended goal programming model for site selection in the offshore wind farm sector," Annals of Operations Research, Springer, vol. 245(1), pages 121-135, October.
    16. Chang, Ching-Ter, 2011. "Multi-choice goal programming with utility functions," European Journal of Operational Research, Elsevier, vol. 215(2), pages 439-445, December.
    17. Oliveira, Washington A. & Fiorotto, Diego J. & Song, Xiang & Jones, Dylan F., 2021. "An extended goal programming model for the multiobjective integrated lot-sizing and cutting stock problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 996-1007.
    18. Özarık, Sami Serkan & Lokman, Banu & Köksalan, Murat, 2020. "Distribution based representative sets for multi-objective integer programs," European Journal of Operational Research, Elsevier, vol. 284(2), pages 632-643.
    19. Bilbao-Terol, Amelia & Arenas-Parra, Mar & Cañal-Fernández, Verónica, 2016. "A model based on Copula Theory for sustainable and social responsible investments," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 55-76.
    20. Natawat Jatuphatwarodom & Dylan F. Jones & Djamila Ouelhadj, 2018. "A mixed-model multi-objective analysis of strategic supply chain decision support in the Thai silk industry," Annals of Operations Research, Springer, vol. 267(1), pages 221-247, August.

    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:spr:annopr:v:267:y:2018:i:1:d:10.1007_s10479-017-2568-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.