Research On Decision Support Method And Application Of Joint Search And Rescue In The Sea Battlefield

With the continuous advancement of our military’s strategic frontier,the focus of future operations will shift from inland to disputed border,the first or the second island chains,maritime strategic channels,and areas where national interests are at stake.Noted that the transition of offensive and defensive sea battles will have a fast pace without obvious front and rear boundaries.Search and rescue(SAR)forces will often carry on tasks with the combat forces in a war zone where they face a more complex battlefield environment.Joint SAR in the sea battlefield is an important support for raining to promote the generation of combat capabilities in peacetime,and for the regeneration and restoration of combat capabilities during wartime.Therefore,under the guidance of goal of building a powerful military in the new era,how to enhance the research on the methods and applications of joint search and rescue assistance in the sea battlefield,help to build a joint SAR system-of-systems(SARSo S)that matches the sea battlefield environment,and improve joint SAR capabilities has become a major issue in our army.At present,due to the high complexity and uncertainty of the joint SARSo S in sea battlefield,it is difficult for researchers and military decision makers to establish an accurate and applicable process and method for sea battlefield joint SARSo S design,and thus cannot complete the scientific planning for the joint SAR schemes.It is also difficult to explain and verify the results of auxiliary decision-making that are usually obtained.This paper aims to research the sea battlefield joint SAR decision-making method and application from three aspects: the design of the sea battlefield joint SARSo S,the SAR risk analysis and evaluation,and the SAR schemes generation and optimization.In order to promote the overall coordinated development of the joint SAR in the sea battlefield,we should ensure that the constructed SARSo S is accurate and applicable,the SAR scheme is effective and feasible.The main research content and innovation points of the thesis can be summarized as follow:First,a research framework is desined for the joint SAR decision support in the sea battlefield.This thesis designs a whole-process decision support framework from the toplevel design of the SARSo S to the risk analysis and assessment,and then to the planning of the joint SAR schemes.The three aspects also correspond to the different levels of the sea battlefield joint SAR decision support method.They are interrelated and progressive,providing a way for the design of the sea battlefield joint SARSo S,SAR risk analysis and evaluation,generation and optimization of SAR schemes.As a feasible method,the framework can also be used to research So S structure design based on multi-views and multi-objective optimization problems.Next,the design method of the joint SARSo S for the sea battlefield based on the multi-views in game perspective is proposed.The sea battlefield joint SARSo S has many important elements,complex correlations and obvious confrontation.This paper takes the establishment of the SARSo S meta-model as the first stage,the graph model for conflict resolution as the bridge,and the multi-view model as the So S description method,forming a new So S design method and theory under the equilibrium of the game which is consistent and satisfactory for decision makers.This method combines the advantages of multi-view model and the conflict resolution theory,and fully considers the preference information of each decision maker.It can effectively solve the group decision-making problem of multi-stakeholder for SARSo S construction in the hostile sea battlefield situation,and provide data foundation and command So S guarantee.Then,a risk analysis and assessment method for joint SAR in the sea battlefield based on multi-source information fusion is proposed.Aiming at the problems of insufficient data,the complex correlation of risk factors,and the different quantification standards,this thesis starts from the multi-source information such as the comprehensive maritime environment,enemy threats,and SAR crew attributes.The hazard,vulnerability and resilience of SAR risk is defined to analysis the network relationship structure of various SAR risk factors based on neural network.Through merging single risk of SAR ship to obtain the whole risk situation information of the sea battlefield,the thesis completes the analysis and assessment of SAR risks from both the overall and partial perspectives and discuss how the individual risks reflect the overall risk,which provides a way for scientifically assessing SAR risks and improves the ability of SAR schemes to resist risks.Last but not least,a multi-objective optimization method for generating and optimizing a joint SAR scheme in the sea battlefield is proposed.According to the unique enemy threat and confrontation characteristics of the sea battlefield,the SAR risk and the comprehensive success rate of SAR are introduced as the main optimization goals for the SAR schemes.The SAR resource allocation model and the SAR area division model are established to help planning SAR process.In addition,the single-objective and multiobjective optimization algorithms are designed,which determines multiple feasible schemes.By simulating the execution process of the SAR schemes,a large amount of decision support information is obtained for SAR planners to consider and choose.This method provides the key processes and technical methods for the automatic generation and optimization of the joint SAR schemes,and the obtained SAR schemes’ details are more clear and operable,which meets the actual needs of SAR planners to control risks and improve the probability of success.