Civil helicopter maritime search and rescue disposal scheme optimization method

Abstract

The invention discloses a civil helicopter maritime search and rescue disposal scheme optimization method, which comprises the steps of initializing a population of a disposal scheme according to parameterized definition and a value range of a task area; performing non-dominated sorting on the species group, and endowing virtual fitness until all individuals are grouped; performing crossover, variation and genetic variation selection operations in the population, and when an optimization result is converged or the number of iterations exceeds a set maximum genetic algebra, outputting a Pareto leading-edge solution set; adding a corresponding search and rescue mode and task property in the task area of each frontier solution set to form a disposal scheme set of helicopter maritime search and rescue; performing simulation deduction according to the sequence, and outputting simulation data of the disposal scheme evaluation indexes under the influence of the uncertain factors through large sample simulation; and performing comprehensive evaluation on the simulation data of each treatment scheme, representing a comprehensive evaluation result in a normal distribution form, and selecting the treatment scheme with the maximum mean value and the minimum variance.

Description

technical field [0001] The invention relates to an auxiliary decision-making support method for helicopter maritime search and rescue, in particular to an optimization method for civil helicopter maritime search and rescue disposal schemes. Background technique [0002] Helicopters are playing an increasingly important role in maritime search and rescue. When an emergency occurs, helicopters will carry out search and rescue missions according to the disposal plan. Therefore, the rationality of the disposal plan largely determines whether the mission is successful. However, there are many uncertainties in maritime search and rescue missions, which lead to a wide distribution of possible locations of distressed targets. It is difficult for traditional methods to formulate a suitable disposal plan to effectively cover the predicted location in the planning stage, and these uncertainties will lead to helicopters according to The task execution effect of the established disposal ...

AI Technical Summary

Problems solved by technology

The disposal plan mainly includes the specific information of the mission area and the specific route to and from the mission area. The former is the main determinant. In the existing mission area planning methods, there are problems that the planning process is inflexible and the optimization result is a local optimal solution.

On the other hand, the existing evaluation methods cannot solve the impact of various uncertain factors on the evaluation results during the implementation of the disposal plan, so it is often difficult to conduct a comprehensive evaluation before executing the task

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