Optimization model for supporting stevedoring activities in maritime ports

• Autor(a) principal: Oliveira, Ana Bernardo
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/23863
• topic: Optimization Modelling; Container Terminal Operations; Berth Allocation and Quay Crane Assignment Problem; Mixed-Integer Linear Programming; Leixões Port Case Study; Port Efficiency

This research conducted between March and September 2023 as part of the Master in Industrial Management and Engineering at the Instituto Superior de Engenharia do Porto, explores the possibility of the application of a quantitative optimization model improving the efficiency in maritime ports. The study focuses on the Berth Allocation and Crane Assignment Problem and how it improves container terminal operations, with a specific focus on Leixões Port in Portugal. The research delves into the challenges faced by container terminals in the global shipping industry and addresses the need for advanced optimization models. The primary goal is to develop a Decision Support System (DSS) made to optimize berth activities in maritime ports, for the efficient allocation of berths and quay cranes in maritime ports. After an extensive literature review, exploring prior-research and concepts that show relevance, an analysis of the existing models and methodologies related to maritime port optimization is carried out. Then, the development of an optimization model tailored to the complexities of maritime port operations is conducted, as well as its validation process by using a range of instances designed to simulate real-world scenarios encountered in port operations. The model was based in Mixed-Integer Linear Programming and incorporates a continuous berth layout and time-invariant Quay Crane assignment. Due to Yilport providing real-world data referring to the first trimester of 2020, it was possible to properly apply the model in a series of scenarios that simulated real-world situations. This dataset enriched the research and served as a foundation for analysis, with a focus on vessel discharge and load operations. After running the model in IBM CPLEX, the methodology of this research aimed for an evaluation of the solutions. Thus, the results consistently revealed a preference for single vessel berthing at the piers, coupled with variations in quay crane deployment and vessel operational times. Furthermore, they indicate that the developed model offers promising improvements in efficiency, as evidenced by reduced operational times, berth occupancy rates, and quay crane utilization rates. It highlights the model's ability to outperform real-world operational times consistently, emphasizing its potential to improve terminal performance and resource allocation. Despite the recognition of certain limitations, such as the model not considering unproductive times, this research contributes valuable insights into optimization modelling within container terminal operations, offering practical implications for enhancing port efficiency. It paves the way for future research in refining models, considering more recent data, and addressing computational challenges to further advance the field of maritime port optimization.