Collaborative Scheduling Optimization of Container Port Berths and Cranes under Low-Carbon Environment

Meixian Jiang, Fangzheng Ma, Yuqiu Zhang, Shuying Lv, Zhi Pei and Guanghua Wu ()
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Meixian Jiang: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Fangzheng Ma: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Yuqiu Zhang: College of Biomedical Science and Engineering, South China University of Technology, Guangzhou 510006, China
Shuying Lv: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Zhi Pei: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China
Guanghua Wu: College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, China

Sustainability, 2024, vol. 16, issue 7, 1-26

Abstract: Motivated by the need for a green and low-carbon economy, we explore the co-scheduling optimization of berths and cranes. Our aim is to balance the carbon tax and operating costs of ports under uncertain conditions, proposing an innovative nonlinear mixed-integer programming formulation. To address this optimization challenge, we have developed an enhanced version of the adaptive spiral flying dung beetle algorithm (ASFDBO). In order to evaluate the performance of the ASFDBO algorithm, we performed a benchmark function test and a convergence analysis with other recognized metaheuristics. In addition, we verified the practical applicability of the ASFDBO algorithm in different test scenarios. Through numerical experiments, we analyze the feasibility and effectiveness of the algorithm’s scheduling solutions and improvement strategies. Results indicate that our collaborative scheduling optimization, which considers both carbon and production costs, achieves feasible solutions and reduces carbon expenses. Finally, we investigate the impact of different carbon tax rates on the joint scheduling optimization of berths and quay cranes, and the results show that a reasonable carbon tax policy can effectively reduce the carbon emissions of ports.

Keywords: carbon tax costs; uncertainty; crane maintenance; adaptive spiral flight dung beetle algorithm; cooperative scheduling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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