# Fuzzy Logic in Selection of Maritime Search and Rescue Units
## 2 Literature Overview (State of the Art)  
Organisation and coordination of SAR operations is equally complex in all sea areas all over the world. To improve the safety of rescue operations, international standard procedures and guidelines have been published in the International Aeronautical and Maritime Search and Rescue (IAMSAR) Manual. The International Maritime Organisation (IMO) promotes the development of enhancements, modifications and activities aimed at improving the effectiveness of SAR operations at sea. The majority of research papers in this field refer to the planning of SAR operation, e.g., modelling of the drift of an object at sea. There is also an increasing amount of research focusing on other aspects such as optimising the deployment of resources, using new technologies and equipment and enhancing the importance of decision support systems in solving maritime rescue problems. Examples of research work on improving the effectiveness of planning and conducting search and rescue operations at sea are given below. For the purpose of supporting the planning and monitoring of rescue operations at sea, a Bayesian network application method is proposed by [5]. For this purpose, the principles for determining the reliability of the raft are presented. In this way, it is possible to assess the safety of the conducted action. This enables more successful action planning. Another example of using mathematical assumptions in relation to maritime rescue is the optimisation algorithm presented in [6]. The discussed algorithm simulates human behaviour during search and rescue operations. The method is applicable to the operation of constraints during problem solving. In the previous articles of the author and co-authors [4; 7] the way of using AIS (Automated Identification System) sensors in rescue operations was presented. The AIS system is used to detect ships and collect data on their parameters. A method of decodingdata from the system has been proposed. In addition, experiments were conducted to select vessels for specific search and rescue operations. Multi-criteria analysis (MDCA) was used for this purpose. Another approach for supporting rescue planning is presented in [8]. The described method allows for optimal allocation of resources in a specific area. The method is based primarily on search theory and gradient search methods. Thanks to this, it is possible to improve the efficiency of planning and reduce the costs of action. The topic of resource allocation is also addressed in [9]. The authors presented a model that takes into account the uncertainty of demand and allows for a balanced distribution of recourses. The method solves the problem for various objective function term weights. The proposed model primarily improves the performance of the SAR system. Another study on resource allocation confirms that the multi-criteria analysis is applicable for search and rescue planning [10]. The model developed allows vessels with different characteristics to be considered. The simulation model is based on historical data and is designed to solve organisational problems. Research on the use of fuzzy logic in decision-making systems is presented in [11]. The study describes a way to distribute personnel for crisis management purposes. A fuzzy expert system and a decision tree were used for this purpose. The model is based on different criteria and, as a result, supports the process of organizing the action. Fuzzy logic principles have also been applied in advanced technology for search and rescue planning. Publication [12] discusses an aspect of using Unmanned Aerial Vehicles for search. The flight path of the drone is determined by calculating the location of the waypoints to be tracked. Another example demonstrating how to combine the principles of multi-criteria analysis and fuzzy logic is [13]. The described case is not related to the field of maritime rescue, but the proposed methodology shows how to support the decision making process when selecting a solution based on several criteria assessment.