摘要
Berth and loading and unloading machinery are not only the mainfactors that affecting the terminal operation, but also the main starting point ofenergy saving and emission reduction. In this paper, a genetic Algorithm Framework is designed for the berth allocation with low carbon and high efficiency atbulk terminal. In solving the problem, the scheduler’s experience is transformedinto a regular way to obtain the initial solution. The individual is represented as achromosome, and the sub-chromosomes are encoded as integers, the roulettewheel method is used for selection, the two-point crossing method is used forcross, and the exchange variation method is used for variation in the procedureof designing the Algorithm. Considering the complexity of berth schedulingproblem and the diversity of constraints and boundary conditions, the geneticalgorithm combines with system simulation to get the final scheme of berthallocation. This model and algorithm are verified to be practical by analyzingmultiple sets of examples of shorelines with different lengths. When comparedwith the traditional algorithms in three aspects which includes berth offsetdistance, departure delay cost and energy consumption of portal crane, the resultindicates that the improved algorithm is more effective and feasible. The studywill help to lower energy consumption and resource waste, reduce environmentalpollution, and provide a reference for low-carbon, green and sustainable development of the terminal.
基金
supported by the project of Zhejiang Federation of Humanities and Social Science in 2022(NO:2022B36)
Xiaona Hu received the grant and URL to the sponsor’s website is https://www.zjskw.gov.cn/.This work is also supported by the Natural Science Foundation of Anhui Province,China(No:2108085MG236)
Gang Hu received the grant and URL to the sponsor’s website is http://kjt.ah.gov.cn/.This work is supported by the Natural Science Foundation from the Education Bureau of Anhui Province,China(No.KJ2021A0385)
Gang Hu received the grant and URL to the sponsor’s website is http://jyt.ah.gov.cn/.
