A heuristic optimization approach for multi-vehicle and one-cargo green transportation scheduling in shipbuilding. (August 2021)

• Record Type: Journal Article
• Authors: Jiang, Zuhua; Chen, Yini; Li, Xinyu; Li, Baihe
• Is Part Of: Advanced engineering informatics. Volume 49(2021)
• Publication Date: 2021-08
• Subjects: Vehicle routing problem -- Green transportation scheduling -- Big-size ship block transportation -- Multi-objective Tabu Search optimization -- Multi-vehicle and one-cargo; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2021.101306
• Languages: English
• ISSNs: 1474-0346

Abstract

Abstract: To actively respond to the call for green shipbuilding, block cooperative transportation has been particularly concerned in reducing carbon emission in the shipyard, and hence a "multi-vehicle and one-cargo" (MVOC) green transportation scheduling problem emerges. Aiming to solve this problem effectively and improve transportation efficiency and reduce energy consumption, a bi-objective mathematical model combined routing model with synchronization constraints is proposed to simultaneously minimize non-value-added transportation time cost and total CO2 emission. A Pareto-based multi-objective Tabu Search (MOTS) algorithm is then designed to solve the model, in which local improvements are developed to generate promising neighboring individuals. Experimental results show that the proposed MOTS algorithm can effectively solve the problem even on a large scale and outperform the classic algorithm of nondominated sorting genetic algorithm-II (NSGA-Ⅱ). It is hoped that this work enables an operation mode with high efficiency and low energy consumption and provides useful insights for flatcar transportation scheduling operators in the shipyard.