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Techno-economic optimization for containership green transition under net-zero emission target: a predict-then-optimize framework

Author

Listed:
  • Zhou, Leqi
  • Jin, Jian Gang
  • Gao, Yuling
  • Iris, Çağatay
  • Bektaş, Tolga
  • Chen, Jiang Hang

Abstract

Shipping companies are under growing pressure to meet net-zero emission target under tightening regulations. To tackle this challenge, this paper extends the techno-economic predict-then-optimize framework to make long-term strategic decisions that jointly minimize greenhouse gas emissions and lifecycle costs over the planning horizon. The framework integrates a vessel-specific fuel consumption prediction model for comprehensive estimation of future emissions, and an optimization model that strategically schedules and combines multiple emission reduction methods. The optimization explicitly accounts for the techno-economic trade-offs among slow steaming, maintenance, fuel switching, and capital investments for retrofits, while ensuring compliance with carbon intensity indicator (CII) regulations and the overall net-zero emission target. A case study on several containerships demonstrates the applicability of the model, with numerical experiments showing that the predict-then-optimize framework achieves a 67% carbon reduction by 2040. Further investigations of the strategies, including illustration of transition plans, comparisons of different strategies, evaluation of marginal costs for each method, and sensitivity analysis on interest rates and regulations, are conducted to provide insights into lifecycle cost-minimizing and emission regulation-compliant strategy design.

Suggested Citation

  • Zhou, Leqi & Jin, Jian Gang & Gao, Yuling & Iris, Çağatay & Bektaş, Tolga & Chen, Jiang Hang, 2026. "Techno-economic optimization for containership green transition under net-zero emission target: a predict-then-optimize framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 209(C).
  • Handle: RePEc:eee:transe:v:209:y:2026:i:c:s1366554526000712
    DOI: 10.1016/j.tre.2026.104731
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