多平台海上协同搜索与路径优化策略研究

针对传统海上搜索研究中搜索平台与行为单一、缺乏协同的问题,建立多平台海上协同搜索路径优化模型,研究协同搜索与路径优化对策.在协同搜索策略方面,给出同构协同与异构协同搜索策略的定义,并设计不同规模的协同仿真场景;在路径优化策略方面,根据海上搜索平台的搜索特点,设计基于行为和基于智能算法的路径优化策略.在此基础上,对比研究不同规模的海上协同搜索策略与路径优化策略效果.结果表明:基于混合智能算法的路径优化效果普遍优于基于行为的搜索策略与单一算法,异构协同搜索策略能够充分发挥各平台优势、取长补短,取得了优于单平台和同构协同搜索的收益效果.

Strategies of maritime cooperative searching and path optimization using multiple platforms

Considering the monotony of the searching platform and the behavior of traditional maritime coverage path planning, as well as the absence of cooperation, this paper establishes the mathematical model for the maritime cooperative searching problem using multiple platforms and researches the strategies of searching cooperation and path optimization. In terms of the cooperative searching, definitions on homogenous and heterogeneous cooperative searching strategies are provided, and simulation scenarios of different scales are designed. In terms of the path optimization, the strategies based on behaviors and intelligent algorithms are designed according to the searching characteristics of different maritime platforms. On that basis, comparisons on effects from various cooperative searching and the path optimization strategies in different maritime scenarios are conducted. It is indicated that the path optimization strategy using hybrid intelligent algorithms presents a superior performance than the behavior-based strategy and the single algorithm. The heterogeneous cooperative searching strategy is probable to take advantages of different platforms while making up their disadvantages, contributing to a higher profit than the single and the homogenous cooperative searching.