A chaos-coupled multi-objective scheduling decision method for liner shipping based on the NSGA-III algorithm. (December 2022)

• Record Type: Journal Article
• Authors: Ma, Weihao; Zhang, Jinfeng; Han, Yueyi; Zheng, Huarong; Ma, Dongfang; Chen, Mingzhang
• Is Part Of: Computers & industrial engineering. Volume 174(2022)
• Publication Date: 2022-12
• Subjects: Multi-objective optimization -- Chaos algorithm -- NSGA-III -- Sailing cost, time and emissions -- Hyperplane-based ranking method; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108732
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Proposed a multi-objective model for determining shipping scheduling decision. Introducing chaotic sequences in NSGAIII algorithm can improve performance. The proposed HYRM method is able to respond according to user preferences. Carbon Emissions trading system is the best shipping carbon tax regulation. Abstract: Reducing sailing costs, time and emissions are three important decision-making objectives for ship operators. In this paper, a multi-objective decision model for liner shipping is established to optimize ship route, speed and number of ships deployed based on the three objectives. Moreover, the above model also takes into consideration the three latest ship emission reduction policies, including Emission Control Area, the 2020 Sulfur Limit Order and maritime Carbon Emission Taxation regulations. To solve the multi-objective scheduling problem, an improved non-dominated sorting genetic algorithm-III (NSGA-III) algorithm based on a chaos mechanism is proposed to find the Pareto solutions. And then a Multi-Criteria Decision Making (MCDM) method, the Hyperplane-based ranking method (HYRM) is developed to find the trade-off solution from the Pareto solutions. The proposed method was applied to two liner shipping service routes around southeast Asia and eastern United States, the results show that the proposed method can simultaneously reduce sailing costs, time and ship emission according to the users' preferences, and it can help shipping companies cope with fuel price fluctuations effectively.