Author
Listed:
- Jianhua Zhou
(Zhoushan COSCO Shipping Heavy Industry Co., Ltd., Zhoushan 316100, China)
- Haifei Wu
(Zhoushan COSCO Shipping Heavy Industry Co., Ltd., Zhoushan 316100, China)
- Hailong Weng
(Zhoushan COSCO Shipping Heavy Industry Co., Ltd., Zhoushan 316100, China)
- Lijun He
(School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China)
- Wenfeng Li
(School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China)
- Taiwei Yang
(Zhoushan COSCO Shipping Heavy Industry Co., Ltd., Zhoushan 316100, China)
Abstract
Background: As a labor-, capital-, and technology-intensive sector, shipbuilding supports water transportation, international trade, and marine development, driving economic growth and employment. Yet rising raw material/labor costs now bottleneck enterprise performance, making cost reduction and efficiency improvement urgent for shipbuilding and repair firms. It is an effective way to improve logistics transportation efficiency for reducing the cost of shipbuilding and repair firms. However, there are still few methods specifically designed for logistics transportation scheduling in shipbuilding and repair firms. Methods: In this paper, a “dual-cycle” strategy is proposed to optimize material transportation and cut logistics vehicles’ empty-load rate in the shipbuilding and repair process. A mixed-integer programming model is built to minimize total empty travel time, considering task priorities and time windows. A genetic algorithm-based scheduling method is proposed to solve this complex scheduling model. Results : Simulation with real shipyard logistics data shows the proposed model and algorithm can effectively address the shipbuilding logistics vehicle scheduling problem. In addition, the proposed algorithm performs better than two other compared algorithms in handling the studied problem. Conclusions: This study aids shipbuilding and repair logistics managers in making scheduling plans and determining optimal vehicle numbers, supporting cost-efficiency improvement.
Suggested Citation
Jianhua Zhou & Haifei Wu & Hailong Weng & Lijun He & Wenfeng Li & Taiwei Yang, 2025.
"Optimization of Engineering Vehicle Scheduling in Shipbuilding and Repair Yards Based on the Dual-Cycle Strategy,"
Logistics, MDPI, vol. 9(4), pages 1-15, November.
Handle:
RePEc:gam:jlogis:v:9:y:2025:i:4:p:163-:d:1799468
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