Evaluation method for helicopter maritime search and rescue response plan with uncertainty

Abstract Helicopter plays an increasingly significant role in Maritime Search and Rescue (MSAR), and it will perform MSAR mission based on response plans when an accident occurs. Thus the rationality of response plan determines the success of MSAR mission to a large extent. However, with the impact of many uncertainty factors, it is difficult to evaluate response plans comprehensively before performing them. Aiming at these problems, an evaluation framework of helicopter MSAR response plan named UMAD is proposed in this paper, which reveals the influence mechanism of uncertainty factors based on Multi-Agent method and analyzes the mission flow based on Discrete Event System (DEVS) method. Furthermore, the evaluation criterion and indicators of response plan are extracted from the aspects of safety and effectiveness. Meanwhile, the Monte Carlo method is adapted to calculate the probability distribution and robustness of response plan comprehensive result. Finally, in order to illustrate the validity of this method, it is discussed and verified by an application example of evaluating multiple response plans to the same MSAR scenario. The results show that this method can analyze the influence of uncertainty more systematically and optimize response plans more comprehensively.

[1]  Thomas L. Saaty,et al.  Marketing Applications of the Analytic Hierarchy Process , 1980 .

[2]  Xindong Peng,et al.  Algorithms for Interval-Valued Pythagorean Fuzzy Sets in Emergency Decision Making Based on Multiparametric Similarity Measures and WDBA , 2019, IEEE Access.

[3]  B.P. Zeigler,et al.  Symbolic discrete event system specification , 1992, IEEE Trans. Syst. Man Cybern..

[4]  Ke Zhang,et al.  Research on Evaluation Model of Maritime Search and Rescue Emergency Management Capabilities Based on Improved Grey Cloud Model , 2018 .

[5]  Ove T. Gudmestad,et al.  Long-Range Rescue Capability for Operations in the Barents Sea , 2013 .

[6]  Xia Zhang,et al.  A probabilistic occupant evacuation model for fire emergencies using Monte Carlo methods , 2013 .

[7]  Zhang Hao,et al.  Comprehensive Evaluation of Maritime Emergency Capability , 2010, 2010 Second International Conference on Computer and Network Technology.

[8]  Huang Jun,et al.  Design space exploration in aircraft conceptual design phase based on system-of-systems simulation , 2015 .

[9]  Chuan Fu Guo,et al.  A Multiple Criteria Decision Method for Selecting Maritime Search & Rescue Scheme , 2012 .

[10]  Dimitri N. Mavris,et al.  Stochastic Agent-Based Analysis of UAV Mission Effectiveness , 2011 .

[11]  Jian Chai,et al.  Emergency rescue planning under probabilistic linguistic information: An integrated FTA-ANP method , 2019, International Journal of Disaster Risk Reduction.

[12]  Niping Jia,et al.  Research on the Search and Rescue System-of-Systems Capability Evaluation Index System Construction Method Based on Weighted Supernetwork , 2019, IEEE Access.

[13]  Qiong Wu,et al.  A Game Theory Based on Monte Carlo Analysis for Optimizing Evacuation Routing in Complex Scenes , 2015 .

[14]  Mumtaz Karatas,et al.  Agent-based model of maritime search operations: A validation using test-driven simulation modelling , 2015, 2015 Winter Simulation Conference (WSC).

[15]  Xu Jing-ha STUDY ON CITY'S EARTHQUAKE EMERGENCY DISPOSAL SCHEME-RELATED TECHNOLOGY , 2014 .

[16]  Hu Liu,et al.  Training effectiveness evaluation of helicopter emergency relief based on virtual simulation , 2018, Chinese Journal of Aeronautics.

[17]  J R Frost,et al.  REVIEW OF SEARCH THEORY: ADVANCES AND APPLICATIONS TO SEARCH AND RESCUE DECISION SUPPORT: FINAL REPORT , 2001 .

[18]  Christophe Maisondieu,et al.  Wind-induced drift of objects at sea: The leeway field method , 2011 .

[19]  Harish Garg,et al.  Algorithms for interval-valued fuzzy soft sets in emergency decision making based on WDBA and CODAS with new information measure , 2018, Computers & Industrial Engineering.

[20]  B. P. Zeigler,et al.  Behavioral characterization of discrete event systems , 1993, 1993 4th Annual Conference on AI, Simulation and Planning in High Autonomy Systems.

[21]  Genichii Taguchi,et al.  Introduction to quality engineering. designing quality into products a , 1986 .

[22]  Huang Jun,et al.  Non-uniform hybrid strategy for architecting and modeling flight vehicle focused system-of-systems operations , 2016 .

[23]  Tsung-chow Su,et al.  On predicting boat drift for search and rescue , 2010 .

[24]  N A Stanton,et al.  Using social network analysis and agent-based modelling to explore information flow using common operational pictures for maritime search and rescue operations , 2013, Ergonomics.

[25]  Yanbing Ju,et al.  Emergency alternative evaluation and selection based on ANP, DEMATEL, and TL-TOPSIS , 2015, Natural Hazards.

[26]  Mumtaz Karatas,et al.  An ILP and simulation model to optimize search and rescue helicopter operations , 2017, J. Oper. Res. Soc..

[27]  Hao Yong,et al.  Capability Evaluation of Maritime Emergency Management System , 2012, 2012 11th International Symposium on Distributed Computing and Applications to Business, Engineering & Science.

[28]  Jie Yao,et al.  Maritime Search and Rescue Capability Evaluation Algorithm Based on Cloud Model , 2014 .