An integrated fuzzy risk assessment for seaport operations http://researchonline.ljmu.ac.uk/id/eprint/1787/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively.Abstract Seaport operations are characterised by high levels of uncertainty, as a result their risk evaluation is a very challenging task. Much of the available data associated with the system's operations is uncertain and ambiguous, requiring a flexible yet robust approach of handling both quantitative and qualitative data as well as a means of updating existing information as new data becomes available. Conventional risk modelling approaches are considered to be inadequate due to the lack of flexibility and inappropriate structure for addressing the system's risks. This paper proposes a novel fuzzy risk assessment approach to facilitating the treatment of uncertainties in seaport operations and to optimize its performance effectiveness in a systematic manner. The methodology consists of a fuzzy analytical hierarchy process, an evidential reasoning (ER) approach, fuzzy set theory and expected utility. The fuzzy analytical hierarchy process is used to analyse the complex structure of seaport operations and determine the weights of risk factors while ER is used to synthesise them. The methodology provides a robust mathematical framework for collaborative modelling of the system and allows for a step by step analysis of the system in a systematic manner. It is envisaged that the proposed approach could provide managers and infrastructure analysts a flexible tool to enhance the resilience of the system in a systematic manner. Keywords: Seaport operations; evidential reasoning approach; fuzzy set theory; fuzzy analytical hierarchy process 2. Literature Review CMI systems are faced with high operational constraints due to the dynamic interactions among their interrelated components. The level of interdependences and complexity of the system's operations can be acknowledged through its description by the US Department of Homeland Security "as all areas and things of, on, under, relating to, adjacent to, or bordering on a sea, ocean, or other navigable waterway, including all maritime related activities, infrastructure, people, cargo, vessels and other conveyances" [8]. Analysing the systems in terms of their interdependences which include infrastructure characteristics, operational relationships, environmental impacts, technical efficiency, failure types and state of operation provides insight into their complexity, enabling collaborative modelling to be undertaken. Modern seaports, which are an integral component of CMI systems, focus their operations on continuous handling of flows and efficient transport. Meersman [9], as shown in Figure 1, revealed that these systems progressed from performing cargo handling, stacking and distribution functions to being a complex transportation hub in logistic chains. A vessel operator controls a fleet of vessels with a set of characteristics; the land si...

Risk analysis in seaports plays an increasingly important role in ensuring port operation reliability, maritime transportation safety and supply chain distribution resilience. However, the task is not straightforward given the challenges, including that port safety is affected by multiple factors related to design, installation, operation and maintenance and that risk-based decision support in container terminals. The proposed approach can also be tailored for wider application in other engineering and management systems, especially when instant risk ranking is required by the stakeholders to measure, predict, and improve their system safety and reliability performance.

Over the years, many efforts have been focused on developing methods to design seaport systems, yet disruption still occur because of various human, technical and random natural events. Much of the available data to design these systems are highly uncertain and difficult to obtain due to the number of events with vague and imprecise parameters that need to be modelled. A systematic approach that handles both quantitative and qualitative data, as well as means of updating existing information when new knowledge becomes available is required.Resilience, which is the ability of complex systems to recover quickly after severe disruptions, has been recognised as an important characteristic of maritime operations. This paper presents a modelling approach that employs Bayesian belief networks to model various influencing variables in a seaport system. The use of Bayesian belief networks allows the influencing variables to be represented in a hierarchical structure for collaborative design and modelling of the system. Fuzzy Analytical Hierarchy Process (FAHP) is utilised to evaluate the relative influence of each influencing variable. It is envisaged that the proposed methodology could provide safety analysts with a flexible tool to implement strategies that would contribute to the resilience of maritime systems.

Globalization has led to a rapid increase of container movements in seaports. Risks in seaports need to be appropriately addressed to ensure economic wealth, operational efficiency, and personnel safety. As a result, the safety performance of a Container Terminal Operational System (CTOS) plays a growing role in improving the efficiency of international trade. This paper proposes a novel method to facilitate the application of Failure Mode and Effects Analysis (FMEA) in assessing the safety performance of CTOS. The new approach is developed through incorporating a Fuzzy Rule-Based Bayesian Network (FRBN) with Evidential Reasoning (ER) in a complementary manner. The former provides a realistic and flexible method to describe input failure information for risk estimates of individual hazardous events (HEs) at the bottom level of a risk analysis hierarchy. The latter is used to aggregate HEs safety estimates collectively, allowing dynamic risk-based decision support in CTOS from a systematic perspective. The novel feature of the proposed method, compared to those in traditional port risk analysis lies in a dynamic model capable of dealing with continually changing operational conditions in ports. More importantly, a new sensitivity analysis method is developed and carried out to rank the HEs by taking into account their specific risk estimations (locally) and their Risk Influence (RI) to a port's safety system (globally). Due to its generality, the new approach can be tailored for a wide range of applications in different safety and reliability engineering and management systems, particularly when real time risk ranking is required to measure, predict, and improve the associated system safety performance.

More than 80% of international cargo moves through seaports, making a contribution to the world economy. As a result, the performance of seafarers plays a major role in the safety of international trade and the maritime environment. This paper presents a novel approach to monitoring the performance of seafarers in terms of their conditional reliability. Unlike a traditional reliability analysis of a seafarer, this approach contains a dynamic model capable of coping with continually changing conditions that affect a seafarer's performance. The proposed methodology enables and facilitates decision makers to assess the performance of a seafarer before his or her designation to any activities and during his or her seafaring period. To evaluate a seafarer's reliability, a generic model is constructed and a combination of different techniques such as fuzzy logic, a fuzzy rule base, an analytical hierarchy process, evidential reasoning, a mapping process and expected utility is used. Furthermore, by changing the conditions that affect the reliability of an ideal seafarer and through calculating a value for this reliability, a benchmark is constructed. A seafarer's reliability depends upon many variables and their dependencies; alteration of a criterion value will ultimately alter a seafarer's reliability. In order to correct any deviation on time, a seafarer's reliability has to be measured appropriately and regularly.