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A Linear Relaxation-Based Heuristic for Iron Ore Stockyard Energy Planning

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  • Marcos Wagner Jesus Servare Junior

    (Electrical Engineering Department, Federal University of Espírito Santo, Av. Fernando Ferrari, 514–Goiabeiras, Vitória, ES 29075-910, Brazil
    Group for Research in Decision Analysis, Hautes Études Commerciales de Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 2A7, Canada)

  • Helder Roberto de Oliveira Rocha

    (Electrical Engineering Department, Federal University of Espírito Santo, Av. Fernando Ferrari, 514–Goiabeiras, Vitória, ES 29075-910, Brazil)

  • José Leandro Félix Salles

    (Electrical Engineering Department, Federal University of Espírito Santo, Av. Fernando Ferrari, 514–Goiabeiras, Vitória, ES 29075-910, Brazil)

  • Sylvain Perron

    (Group for Research in Decision Analysis, Hautes Études Commerciales de Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 2A7, Canada)

Abstract

Planning the use of electrical energy in a bulk stockyard is a strategic issue due to its impact on efficiency and responsiveness of these systems. Empirical planning becomes more complex when the energy cost changes over time. The mathematical models currently studied in the literature consider many actors involved, such as equipment, sources, blends, and flows. Each paper presents different combinations of actors, creating their own transportation flows, thus increasing the complexity of this problem. In this work, we propose a new mixed integer linear programming (MILP) model for stockyard planning solved by a linear relaxation-based heuristic (LRBH) to minimize the plan’s energy cost. The proposed algorithm will allow the planner to find a solution that saves energy costs with an efficient process. The numerical results show a comparison between the exact and heuristic solutions for some different instances sizes. The linear relaxation approach can provide feasible solutions with a 3.99% average distance of the objective function in relation to the optimal solution (GAP) in the tested instances and with an affordable computation time in instances where the MILP was not able to provide a solution. The model is feasible for small and medium-sized instances, and the heuristic proposes a solution to larger problems to aid in management decision making.

Suggested Citation

  • Marcos Wagner Jesus Servare Junior & Helder Roberto de Oliveira Rocha & José Leandro Félix Salles & Sylvain Perron, 2020. "A Linear Relaxation-Based Heuristic for Iron Ore Stockyard Energy Planning," Energies, MDPI, vol. 13(19), pages 1-18, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5232-:d:424975
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    References listed on IDEAS

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    1. Dafnomilis, I. & Duinkerken, M.B. & Junginger, M. & Lodewijks, G. & Schott, D.L., 2018. "Optimal equipment deployment for biomass terminal operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 147-163.
    2. Unsal, Ozgur & Oguz, Ceyda, 2019. "An exact algorithm for integrated planning of operations in dry bulk terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 103-121.
    3. Thomas Kalinowski & Reena Kapoor & Martin W. P. Savelsbergh, 2017. "Scheduling reclaimers serving a stock pad at a coal terminal," Journal of Scheduling, Springer, vol. 20(1), pages 85-101, February.
    4. Menezes, Gustavo Campos & Mateus, Geraldo Robson & Ravetti, Martín Gómez, 2017. "A branch and price algorithm to solve the integrated production planning and scheduling in bulk ports," European Journal of Operational Research, Elsevier, vol. 258(3), pages 926-937.
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    1. Álvaro D. O. Lopes & Helder R. O. Rocha & Marcos W. J. Servare Junior & Renato E. N. Moraes & Jair A. L. Silva & José L. F. Salles, 2023. "Planning an Integrated Stockyard–Port System for Smart Iron Ore Supply Chains via VND Optimization," Sustainability, MDPI, vol. 15(11), pages 1-20, June.

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