鱼群算法求解无人机任务规划问题

无人机任务规划问题是一个NP难问题,文中提出了一种带禁忌算子的鱼群算法对该问题进行求解.鱼群算法是在群体智能行为研究基础上提出的一种新型仿生优化算法,该算法根据"水域中鱼生存数目最多的地方一般就是该水域中富含营养最多的地方"这一特点来模拟鱼群的觅食行为以实现全局最优.文章在基本鱼群算法FSA的基础上,结合禁忌搜索的思想,对基本鱼群算法中的三种行为算子进行改进,在每种行为算子中增添对解领域的禁忌搜索规则,提出带禁忌算子的鱼群算法(FSAWTS).然后将该算法应用于无人机任务规划问题.仿真试验表明,与基本鱼群算法相比,改进后的鱼群算法能够更为有效得解决无人机任务规划问题.

A FSA with Tabu Search for UAV Mission Planning Problem

Unmanned Aerial Vehicle(UAV) mission planning problem is a NP hard problem.A Fish Search Algorithm with Tabu Search(FSAWTS) is presented to solve this problem.Fish Search Algorithm(FSA) is a new bionic approach improved on the base of colony intelligence research.FSA finds the global optimal solution by simulating a trait of fish,which is stated as" the place that holds the greatest number of fish is where the largest amount of alimentation stays".Combining the idea of tabu search with FSA,this paper presents a FSAWTS,in which tabu search principle is introduced to three basic operators in FSA.Thus the optimization ability of the algorithm is improved.Then FSAWTS is applied to solve UAV mission planning problem.Simulation results confirm that the performance of FSAWTS is better than that of FSA,and FSAWTS can solve UAV mission planning problem effectively.