From a scientific viewpoint, as well as from the perspective of navigation practice, it is clear that the Adriatic Sea feeder service is relatively underdeveloped. Hence, the objective of this study is to suggest a model for selecting the hub port and to optimize the network of seaports engaged in the feeder service. Accordingly, an appropriate hub port has been identified through the methods of multi-criteria decision making and expert assessment, and the optimum shipping route has been calculated by applying the travelling salesman algorithm (TSA). In order to analyze whether there is a possibility of obtaining better optimization results, an integration of a sub-hub port system is suggested. Optimization has been achieved by applying a minimum spanning tree algorithm (MST) and a combination of these algorithms. The proposed methodology for selecting the hub port, sub-hub port and optimizing the feeder network can be implemented globally. The practical application of the achieved model would result in cost minimization, owing to shorter shipping routes or a combination of different transportation means (feeders).
The common practice in world-wide ports is that they have determined procedures regarding number of required tugs depending usually on most important factors such as weather criteria and size of vessel. This article presents various rules for some ports which is defined in their Safety Management System and criteria in choosing optimum number of tugs and optimum bollard pull. It is also described how various towage requirements can be assessed through the use of maritime simulators and which parameters are important and how the same can be obtained and assessed. General guidelines will also be defined in the article which must be taken into consideration for optimal choosing of tug boats. The science method used in this article is known as comparative analyses between computation and simulation on simulator; results are presented in figure 10.
According to the Convention for the Safety of Life at Sea and International Convention on Maritime Search and Rescue, saving human lives at sea is the duty of all signatory states. This paper analyzes and gives an overview of previous research activities in search and rescue system at sea and how the use of unmanned aerial vehicles (UAV) can improve search and rescue actions at sea. Research activities include development of the search system and placement of resources that are used in search and rescue actions (ships, planes etc.). Previous research is mainly related to minimizing response time when accidents at sea are detected in relation to search and rescue missions. Implementation of unmanned aerial vehicles into the search and rescue system enables improvement of these actions due to earlier detection and verification of accidents at sea and prevents unnecessary search and rescue units engagement in cases when an accident did not occur. The results of previous research point to the fact that future research should aim to explore the synthesis of unmanned aerial vehicles with the existing search and rescue system at sea in Croatia.
Given the fact that every maritime venture is exposed to continuous risks, it is necessary to create a hierarchic structure of its predictors and to manage them efficiently. In view of that, the International Maritime Organization (IMO) suggests the possibility of risk management through the Formal Safety Assessment (FSA). The key element in the implementation of this method is to determine the optimum point of investment in risk reduction with the purpose of achieving the balance between the costs of protective measures and the profit. Although it may be inappropriate to discuss the price of a human life, it is nevertheless possible to calculate it by formal mathematical procedures through the Cost of Averting a Fatality (CAF) and the Implied Cost of Averting a Fatality (ICAF). This methodology has allowed to produce-and to present in this paper-the above values for the Republic of Croatia for the very first time. In addition, by using the ϰ2 test, it has been possible to examine the relations between the observed actions (foundering, collision / impact, flooding, fire, disabled and adrift, man overboard) and the period (years 2006-2017). The results clearly show a statistically relevant dependence (ϰ2(88)=143,17; p<0,001) among the observed categories, which probably results from various implementation dynamics of the risk reduction measures that are performed in Croatia on a yearly basis. The results obtained by this research can provide important additional guidelines for the optimisation of the risk management model. Sažetak Uzimajući u obzir činjenicu da je svaki plovidbeni pothvat izložen kontinuiranom riziku, nužno je na odgovarajući način hijerarhijski strukturirati njegove prediktore te njima optimalno upravljati. U skladusa spomenutim, IMO (eng. International Maritime Organization) nudi mogućnost upravljanja rizikom uz pomoć Formalne procjene sigurnosti (eng. Formal Safety Assessment-FSA). Pritom je ključan element implementacije te metode određivanja optimalne točke ulaganja u smanjenje rizika s ciljem postizanja ravnoteže troškova zaštitnih mjera i dobiti. Iako je neprikladno govoriti o cijeni ljudskog života, ona se formalnim matematičkim postupcima izračunava putem cijene sprečavanja pogibelji (eng. Cost of Averting a Fatality-CAF), te pretpostavljene cijene sprječavanja pogibelji (engl. Implied Cost of Averting a Fatality-ICAF). U radu su korištenjem prikladne metodologije po prvi put izračunate spomenute vrijednosti za Republiku Hrvatsku. Dodatno, korištenjem ϰ2 testa, ispitana je zavisnost broja promatranih akcija (tone, sudar/udar, naplavljivanje, požar, onesposobljen i pluta, čovjek u moru) i godine (2006.-2017.). Rezultati jasno pokazuju postojanje statistički značajne zavisnosti (ϰ2(49)=152,57; p<0,001) promatarnih kategorija, što je vjerojatno posljedica različitih implementacijskih dinamika mjera za smanjenje rizika koje se u Hrvatskoj provode na godišnjoj bazi. Rezultati ovog istraživanja mogu dati važne dodatne smjernice optimizaciji modela upravljanja rizikom. KEY WORDS risk management ...
Abstract.Recently, during search and rescue actions at sea, Unmanned Aerial Vehicles (UAVs) have been used. Onboard decision capabilities allow an UAV vehicle to reach the entity that is in distress at sea. UAVs are launched within a few minutes to begin search actions. When the exact location of the injured entity is detected, a rescue action should begin. According to the collected information about the vessel's position, manoeuvrability, and velocity, the control centre determines which vessel is to be engaged in the rescue action. This highly autonomous system can be described as a discrete event system. Certain states of such systems, such as collisions, are undesirable. This paper presents implementation of information flow to supervise, control, and monitor the behaviour of the UAVs during the search, to avoid collisions and to communicate with computational onboard sub-systems. Planning algorithms and coloured Petri nets are used to specify different phases of the mission execution. When a certain UAV detects an injured entity, alternative encoded reactions are triggered and a control centre starts implementing the rescue plan. IntroductionUnmanned Aerial Vehicles (UAVs) are becoming a very important tool for Search and Rescue (SAR) operations at sea (Skrzypietz 2010). As it is known, time is critical for saving human life at sea, so any delay can result in potential losses of human 28 Dario Medić, Anita Gudelj, Maja Krčum life. For SAR operations, UAV can be fitted with high resolution cameras, multispectral sensor, thermal sensor, infrared sensors (IR), and hyperspectral sensors. According to the development of UAVs to this date, they can be airborne from one hour to more than 24 hours. It is a known fact that UAVs can be controlled in two ways: at distance and by their previously set route. For the purpose of this paper, UAVs that fly according to their previously set route will be analyzed.Systems with multiple UAVs present significant advantages in different applications by increasing efficiency, performance, and robustness (Alejo et al. 2013, Maza et al. 2011.Some of the problems that need to be solved are: a) How to control the traffic in a way that UAVs moving in opposite directions make as few stops as possible during the passage through the cells in the space? b) How to resolve possible conflicts in case that more vehicles try to acquire the same cell at the same time? c) How to avoid possible deadlocks in the dense traffic?The vehicle's moving through the cells in the space can generally be described as a set of discrete states and events (discrete event dynamic systems -DEDS). These events and states are normally observed by the UAV management system (UAVMS) which receives data from Air Traffic Management systems (ATM), using wireless data communication. Some of these states, such as conflicts and deadlocks are undesirable. In Kezić et al. (2010), the authors used DEDS and Petri net (PN) theory, a well-known tool for analyzing DEDS to resolve some of the above-mentioned problems.In this paper...
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