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<p>Capacity allocation is a crucial decision in production, particularly for sustainable products such as reusable items, where consumer demand is highly uncertain due to the risks associated with adopting new products. Governments usually implement environmentally friendly policies to encourage the purchase of such goods. Consequently, a company should consider policy decisions early in the capacity allocation stage to ensure greater effectiveness. In this paper, a two-stage stochastic programming model. In the first stage, the capacity is determined for each assembly center. In the second stage, after observing the adoption of new products (based on consumer demand scenarios), the environmental policy plan is developed. To comprehensively and objectively evaluate the four carbon policies, a multi-criteria decision-making (MCDM) framework technique based on the method for ordering preference based on similarity to the ideal solution (TOPSIS) was developed. The primary objective is to maximize profit while evaluating the impact of various carbon policies on both profitability and carbon emissions. Four mathematical models are developed under different carbon policies, namely a carbon-free policy, a carbon tax policy, a carbon emissions policy, and a carbon minimization policy, where fuzzy goal programming(FGP) is applied to solve the problem. Finally, a numerical example based on reusable frameworks for car-sharing vehicles demonstrates the feasibility of the model. The results show that under the carbon emission reduction policy, on average, each incremental increase in assembly centers is associated with a 12% increase in profits and a 5% decrease in carbon emissions. This suggests that expanding the number of assembly centers not only improves economic performance but also leads to more sustainable and environmentally efficient production outcomes. Among the four policies, the carbon tax and carbon emission reduction policies provide the most balanced outcomes between economic and environmental objectives. The findings provide valuable insights for policymakers and manufacturers in achieving sustainable production planning under uncertainty.</p>

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Carbon Policy Assessment in Sustainable Product Development: A Two-Stage Stochastic Programming Model Addressing Uncertain Market Demands

  • 期刊论文

  • 发表日期：

    2026年3月25日

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  • Matin Ghanbari Marneh,
  • Mariam Ameli

摘要

Capacity allocation is a crucial decision in production, particularly for sustainable products such as reusable items, where consumer demand is highly uncertain due to the risks associated with adopting new products. Governments usually implement environmentally friendly policies to encourage the purchase of such goods. Consequently, a company should consider policy decisions early in the capacity allocation stage to ensure greater effectiveness. In this paper, a two-stage stochastic programming model. In the first stage, the capacity is determined for each assembly center. In the second stage, after observing the adoption of new products (based on consumer demand scenarios), the environmental policy plan is developed. To comprehensively and objectively evaluate the four carbon policies, a multi-criteria decision-making (MCDM) framework technique based on the method for ordering preference based on similarity to the ideal solution (TOPSIS) was developed. The primary objective is to maximize profit while evaluating the impact of various carbon policies on both profitability and carbon emissions. Four mathematical models are developed under different carbon policies, namely a carbon-free policy, a carbon tax policy, a carbon emissions policy, and a carbon minimization policy, where fuzzy goal programming(FGP) is applied to solve the problem. Finally, a numerical example based on reusable frameworks for car-sharing vehicles demonstrates the feasibility of the model. The results show that under the carbon emission reduction policy, on average, each incremental increase in assembly centers is associated with a 12% increase in profits and a 5% decrease in carbon emissions. This suggests that expanding the number of assembly centers not only improves economic performance but also leads to more sustainable and environmentally efficient production outcomes. Among the four policies, the carbon tax and carbon emission reduction policies provide the most balanced outcomes between economic and environmental objectives. The findings provide valuable insights for policymakers and manufacturers in achieving sustainable production planning under uncertainty.