Letian Wu

Mr. Letian Wu

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
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JYJicheng Yang
Jicheng Yang
LWLetian Wu
Letian Wu
JZJian Zheng
Jian Zheng
Ship weather routing has always been an important issue in the research field of navigation, and many scholars have been devoted to this research for a long time. To study the route strategies of different shipping companies, this paper proposes an improved multi-objective ant colony optimization (IMACO) algorithm based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). It can comprehensively consider ship navigation risk and fuel consumption cost under complex sea conditions. First, the grid method is used to model the marine environment. Then, we calculate the fuel consumption and the ship navigation risk of each grid and use the TOPSIS method to evaluate these two indicators for each grid. The results show that due to the different strictness of navigation management requirements of different companies, different routes are selected in the same sea area at the same time. Compared with the single-objective ant colony optimization (SACO) algorithm, the algorithm proposed in this paper can more comprehensively and effectively solve the problem of route strategy selection of shipping companies, which has great practical significance for ship operations management.

Verified
Journal Article
Open access
PDF file
LWLetian Wu
Letian Wu
CWChuanxu Wang
Chuanxu Wang
This study examines shipping efficiency and its influencing factors in 19 Chinese port cities using a four-stage bootstrap DEA approach. Infrastructure, asset investment, and labor are selected as its inputs; cargo throughput and cargo turnover are selected as the outputs. First, in the three-stage DEA model, the SFA regression method is used to eliminate the impact of external environmental factors and random factors on shipping efficiency. Furthermore, the Bootstrap DEA method is applied to correct deviation to solve the problem of the traditional DEA method being sensitive to the number of variables of a chosen sample. Finally, the real shipping efficiency of the port cities is measured. The empirical results show that the shipping efficiency of each port city is affected by the factors of foreign trade, population size, economic development, consumption level, and government support. Additionally, the average efficiency values of port cities in the eastern region is higher than the general average at each stage; on the contrary, the average efficiency values in the central and western regions are lower than the general average. Finally, the study provides policy implications for the future improvement of shipping efficiency.