Maritime transport is the backbone of international trade of goods. Therefore, seaports are of great importance for maritime transport. Container transport plays an important role in maritime transport and is increasing year by year. Containers transported to a container terminal are stored in container yards side by side and on top of each other, forming blocks. If a container that is not on top of the block has to be retrieved, the containers that are above the required container must be relocated before the required container is retrieved. These additional container relocations, which block the retrieval of the required container, slow down the entire retrieval process. The container relocation problem, also known as the block relocation problem, is an optimization problem that involves finding an optimal sequence of operations for retrieving blocks (containers) from a container yard in a given order, minimizing additional relocations of blocking containers. In this paper, the focus is on the two-dimensional, static, offline and the restricted container relocation problem of real-size yard container bays. A new method for resolving the container relocation problem that uses a genetic algorithm is proposed to minimize the number of relocations within the bay. The method is evaluated on well-known test instances, and the obtained results are compared with the results of various relevant models for resolving the container relocation problem. The results show that the proposed method achieves the best or the second-best result for each test instance within the test set.

The growth of container transport places increasing demand on traffic, especially in situations where container terminals are located near the city centers. The main problem is traffic congestion on networks caused by the integration of Heavy-Duty Vehicles and urban traffic flows. The main objective is to identify the critical traffic parameters which cause negative organizational and environmental impacts on the existing and future traffic demand. A micro-level traffic simulation model was implemented for the testing of the proposed framework-based supply, demand, and control layers. The model was generated and calibrated based on the example of a mid-size Container Terminal “Brajdica” and the City of Rijeka, Croatia. The results indicate that the critical parameters are Queue Length on the approach road to the Container Terminal and the Stop Delay on the main city corridor. High values of these parameters cause negative effects on the environment because of increased fuel consumption and the generation of extra pollution. Due to this problem, a sensitivity analysis of the traffic system performance has been conducted, with a decrement of Terminal Gate Time distribution by 10%. After re-running simulations, the results indicate the impact of subsequent variation in Terminal Gate Time on the decrease of critical parameters, fuel consumption, and vehicle pollution.

The objective of this research is to analyse smart technologies implemented in Croatian marinas and their impact upon the safety and service quality improvement, sustainability, and environmental protection, as well as energy consumption and operations optimisation. Key performance indicators and a definition of smart marina concept have been derived based on the smart port concept. The analysis has been conducted on a sample of 78 marinas in six different counties along the Croatian coast. Ultimately, the SWOT analysis has been performed in order to determine the advantages and disadvantages of introducing smart technologies in marina management. The results indicate that the Croatian marinas are undergoing a revolution in terms of facilitating booking management process and achieving greater safety and service quality, but still need to improve in the field of monitoring and controlling nautical tourism impact upon the environment.

The optimization of seaside operations at container terminals includes solving standard berth and crane allocation problems. The question arises about the efficiency of such optimizations in small and medium-sized container terminals, with different quay designs or different terminal layouts. This paper focuses on developing an integrated model that would apply to medium-sized terminals with a multi-quay layout. The main objectives are determining the shortest possible vessel stay at the port and providing a high-reliability service to ship operators. The developed integrated model includes the optimization process in three stages: initiation, assignment, and adjustment. The model’s main feature is generating operational scenarios based on the cargo distribution onboard and integrated berth and crane allocation. The aim is to choose the most favorable option to optimize ships’ overall processing time in the planning horizon. The experiment was conducted to test the model’s functionality and justify the results by comparing the results obtained by the integrated model with the classical approach of berth and crane allocation in a multi-quay environment. The results show significant improvements in peak periods when ships’ arrivals are concentrated in smaller time intervals by applying the integrated model.

The paper examines the sampling effectiveness of seabin devices and the composition of floating marine litter in port areas. Sampling was carried out from May to September 2021 in Port of Cristo and Port of Colonia de Sant Jordi on Mallorca Island, Spain. This is the first study of the composition of floating marine litter in the ports of Mallorca collected by seabin devices. During the study, 15,899 items and 336 kg of litter were collected and analyzed. The results indicate that seabin effectively collects floating litter from sea surfaces different in size (2 mm to 40 cm). Microplastics (60.8%) were the most commonly found litter, followed by soft plastic items > 5 mm (11.6%) and unidentified hard plastic items > 5 mm (9.6%). Significantly more marine litter was collected in the Port of Cristo (78.6%), compared to the collection of one device in the Port of Colonia de Sant Jordi (21.4%). Time series analysis showed that the average seasonal component was highest in May (68% above baseline). The linear time trend with an R2 of 52.25% indicated the acceptable significance of the model.

The tasks of an officer of the watch (OOW) on complex ships during navigation in coastal areas may be very challenging. Almost all the tasks require substantial information processing and timely decision making. Every distracting element should be avoided during navigation. Every call, made through any communication system, activates a new process that the OOW needs to conduct. The new process may interrupt a previously started task. In case of too many incoming calls, the workload of the OOW may increase significantly, thus, their situational awareness may be compromised and the risk of errors may increase. The objective of this research was to analyze the impact of incoming voice calls on the OOW. The research methods used include a questionnaire survey and a series of interviews with experienced officers. The main outcomes refer to the average frequency of incoming calls, duration of conversations and subjective assessment of their influence. The results indicate that, during one watch, an officer needs to answer 14 calls that last 16.19 min altogether. However, the officers consider 45% of calls made during watch keeping as distracting. A possible call management system with the aim to reduce distractions made by low priority calls is proposed in this paper.