Production planning, which traditionally focused on balancing supply and demand while considering make-to-stock versus make-to-order strategies and capacity constraints, now also must navigate the complexities of carbon trading and achieving carbon neutrality, as emission caps compel companies to trade permits or offsets for compliance. This research developed a novel production planning model for industries dealing with carbon emission limits and allowance trading. The model planned production for specific periods using alternative technologies with varying production costs and carbon emissions. The model considered the government’s allocated emission permits per period, emission allowance price, unit production cost, and unit emission of each technology. Aiming to minimize total costs, the decision variables of the model were the optimal production quantities using each technology per period and the amount of emissions bought or sold. Numerical experience proved that the proposed model was an effective tool for optimally choosing the usage of each technology, thereby minimizing both production and emission costs.

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An Aggregate Production Planning Model Under Carbon Trading Constraints for Sustainable Operations

  • Dwi Kurniawan,
  • Shunichi Ohmori,
  • Qian Huang,
  • Alex J. Ruiz Torres

摘要

Production planning, which traditionally focused on balancing supply and demand while considering make-to-stock versus make-to-order strategies and capacity constraints, now also must navigate the complexities of carbon trading and achieving carbon neutrality, as emission caps compel companies to trade permits or offsets for compliance. This research developed a novel production planning model for industries dealing with carbon emission limits and allowance trading. The model planned production for specific periods using alternative technologies with varying production costs and carbon emissions. The model considered the government’s allocated emission permits per period, emission allowance price, unit production cost, and unit emission of each technology. Aiming to minimize total costs, the decision variables of the model were the optimal production quantities using each technology per period and the amount of emissions bought or sold. Numerical experience proved that the proposed model was an effective tool for optimally choosing the usage of each technology, thereby minimizing both production and emission costs.