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A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains

Author

Listed:
  • Shiyu Chen

    (Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano, Italy)

  • Wei Wang

    (Department of Mechanical Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China)

  • Enrico Zio

    (Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano, Italy
    Aramis Srl, Via Pergolesi 5, 20121 Milano, Italy
    MINES ParisTech, PSL Research University, CRC, 06904 Sophia Antipolis, France)

Abstract

The work presents a simulation-based Multi-Objective Optimization (MOO) framework for efficient production planning in Energy Supply Chains (ESCs). An Agent-based Model (ABM) that is more comprehensive than others adopted in the literature is developed to simulate the agent’s uncertain behaviors and the transaction processes stochastically occurring in dynamically changing ESC structures. These are important realistic characteristics that are rarely considered. The simulation is embedded into a Non-dominated Sorting Genetic Algorithm (NSGA-II)-based optimization scheme to identify the Pareto solutions for which the ESC total profit is maximized and the disequilibrium among its agent’s profits is minimized, while uncertainty is accounted for by Monte Carlo (MC) sampling. An oil and gas ESC model with five layers is considered to show the proposed framework and its capability of enabling efficient management of the ESC sustained production while considering the agent’s uncertain interactions and the dynamically changing structure.

Suggested Citation

  • Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2684-:d:550123
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    References listed on IDEAS

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