Open Access

ARTICLE

An Improved Genetic Algorithm for Berth Scheduling at Bulk Terminal

by Xiaona Hu^1,2, Shan Ji³, Hao Hua⁴, Baiqing Zhou^1,*, Gang Hu⁵

1 Huzhou Vocational & Technical College, Huzhou, 313000, China
2 Shanghai Maritime University, Shanghai, 201306, China
3 Zhengde Polytechnic, Nanjing, 211106, China
4 SKEMA Business School, Lille, 59777, France
5 College of Management Science and Engineering, Anhui University of Technology, Ma’anshan, 243002, China

* Corresponding Author: Baiqing Zhou. Email:

Computer Systems Science and Engineering 2022, 43(3), 1285-1296. https://doi.org/10.32604/csse.2022.029230

Received 28 February 2022; Accepted 06 April 2022; Issue published 09 May 2022

Abstract

Berth and loading and unloading machinery are not only the main factors that affecting the terminal operation, but also the main starting point of energy saving and emission reduction. In this paper, a genetic Algorithm Framework is designed for the berth allocation with low carbon and high efficiency at bulk terminal. In solving the problem, the scheduler’s experience is transformed into a regular way to obtain the initial solution. The individual is represented as a chromosome, and the sub-chromosomes are encoded as integers, the roulette wheel method is used for selection, the two-point crossing method is used for cross, and the exchange variation method is used for variation in the procedure of designing the Algorithm. Considering the complexity of berth scheduling problem and the diversity of constraints and boundary conditions, the genetic algorithm combines with system simulation to get the final scheme of berth allocation. This model and algorithm are verified to be practical by analyzing multiple sets of examples of shorelines with different lengths. When compared with the traditional algorithms in three aspects which includes berth offset distance, departure delay cost and energy consumption of portal crane, the result indicates that the improved algorithm is more effective and feasible. The study will help to lower energy consumption and resource waste, reduce environmental pollution, and provide a reference for low-carbon, green and sustainable development of the terminal.

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Keywords

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