Port logistics (PL) can be defined as the process of planning, implementing and controlling the flow of goods and information between the sea and inland via ports and the other way around. PL systems concern the development of functions to support activities including sea side and land side transportation, cargo storage, order processing, and distribution. Increasing demand and a highly competitive market have forced PL systems to continuously improve their performance, including their operational efficiency and reliability. A key issue is the improvement of decision-making abilities. Decision-making systems play an important role within PL systems, especially as they consider the ways that different processes, operations, and equipment can be controlled and coordinated. With the support of ICT technologies, the decision-making systems have significantly developed. However, several decision making processes lack sufficient ICT support. As a result, the benefits of integrating new ICT supports are unknown, including their benefits for inland vessel coordination and the equipment reliability assessments. The goal of this thesis is to develop an ICT framework to support the decision-making processes and ultimately improve the performance of PL systems. To do so, a hierarchical ICT framework is designed, which consists of two major components: a middleware and an intelligent decision-making approach. With regards of selecting middleware, an agent system is chosen. Likewise, for the selection of intelligent decision making approach, the meta-heuristics approach is chosen to aid the collaborative planning, whereas context-aware system is chosen for the reliability assessment. To further integrate the selected ICT technologies, a hierarchical framework is designed, which contains three layers: an agent model layer, an agent control layer, and an agent management layer. At the agent model layer, the problems are decomposed and modelled as an agent. At the agent control layer, a coordinate agent is integrated with the intelligent decision-making approach to establish control and coordination. Finally, at the agent management layer, the agent communication facility is established...@en

Innovations of information and communication technology (ICT) open plenty opportunities to promote internal operation efficiency and external service level in logistics. As current logistics developments tend to be more complex in operation and large in scale, recent practices start to pay more attentions on improving asset (e.g. equipment and infrastructure) management performance with new ICT development. One of the primary concern is to improve system robustness and reliability. It not only requires the supervision system be capable of diagnosing the condition of the system, but also proficient to find the intrinsic relationship between different conditions and resources thus lead to an integrated decision making process. Moreover, recent ICT innovations, such as WSN and IOT, could record and deliver system descriptors (physical measurements, virtual resources, operational configurations) in real time. Such large-stream and heterogeneous data requires an integrated framework to process and management. To address such challenges, in this paper, a novel concept of context-aware supervision is proposed. An intelligent system with integration of semantic web and agent technology is developed, which aims at providing condition-monitoring and maintenance decisions to relevant user. A generic ontology-agent based framework will be illustrated. The developed system will be applied for the supervision of a large-scale material handling system-belt conveying system as a proof-of-concept.@en

The use of Information and Communication Technology (ICT) has touched various aspects in the domain of transport engineering and logistics (TEL). As the development of TEL tends to be more complex in operation and large in scale, recent practices start to pay more attentions on improving system robustness and reliability. In addition, current ICT innovations (such as WSN and IOT) could record and deliver system descriptors (physical measurements, virtual resources, operational configurations) in real time. Such large-stream and heterogeneous data requires an integrated framework to process and management. To address such challenges, in this paper, a novel concept of context-aware supervision is proposed. An intelligent system with integration of semantic web and agent technology is proposed to support the concept realization, which aims at providing condition-monitoring and maintenance service to relevant user. A generic ontology-agent based framework will be illustrated. Finally, it will be applied for the supervision of a large-scale material handling system- belt conveying system as a proof-of-concept.@en