Optimization applications in seaport container terminal operations and fuzzy logic-based inter terminal trucking

Abstract

Operations research techniques have helped optimize container terminal operations over the past decades and have been a regular feature of maritime logistics and maritime supply chain literature in addition to being in practice at container terminals across the globe. The first phase of the project, a systematic review systematically collates through Scopus and analyzes 1631 papers published in the domain to find the main research clusters and understand future research directions. Studies based on both quayside and landside planning are encapsulated for this research. Five research clusters that discuss simulation, scheduling and automation, quayside operations, integrated operations, and container transportation are identified based on author keywords of the systematically derived paper pool. In addition to that, the evolution of applying optimization techniques in container terminal operations planning is discussed in this study alongside the suggested trajectory of the research agenda under each cluster. The analysis finds that genetic algorithms, integer linear programming and heuristics are the most widely used operations research techniques in container terminal optimization. The review proposes the application of methods such as neural network, fuzzy logic and deep learning models related to artificial intelligence to widen our understanding of container terminal operations. The second phase of the project is conducted to optimize ITT truck flows in container terminals by following the research direction that is derived through the cluster, container transportation in the systematic review. The proposed model is developed using fuzzy logic in MATLAB software. The model can allocate ITT trucks based on the demand from terminal yards and current truck arrival rates at gatehouses. More industry and academia as well as inter-terminal collaborations are needed in future studies for enhancing ITT operations and the overall operations in container terminals.