本文選題：無人機(jī) + 多任務(wù)分配��； 參考：《電光與控制》2017年01期

【摘要】：對多無人機(jī)協(xié)同多任務(wù)分配優(yōu)化問題的目標(biāo)函數(shù)構(gòu)建進(jìn)行研究。多無人機(jī)協(xié)同多任務(wù)分配模型的兩個(gè)主要目標(biāo)函數(shù)(無人機(jī)團(tuán)隊(duì)總飛行航程最小化和執(zhí)行完所有任務(wù)時(shí)間最小化)都有各自的局限性,且兩個(gè)指標(biāo)函數(shù)存在利益沖突。通過為兩個(gè)指標(biāo)函數(shù)分配權(quán)重,建立融合兩個(gè)指標(biāo)函數(shù)的新指標(biāo)函數(shù),采用離散粒子群算法對協(xié)同多任務(wù)分配模型進(jìn)行求解。通過調(diào)節(jié)權(quán)重的大小,可以適應(yīng)不同的戰(zhàn)場環(huán)境,使得兩個(gè)指標(biāo)函數(shù)都得到優(yōu)化。仿真結(jié)果驗(yàn)證了所提方法的有效性。
[Abstract]:The objective function construction of multi-UAV cooperative multi-task assignment optimization problem is studied. The two main objective functions of multi-UAV cooperative multi-task assignment model (UAV team total flight range minimization and mission completion time minimization) have their own limitations and the two index functions have conflict of interest. By assigning weights to two index functions, a new index function combining two index functions is established, and discrete particle swarm optimization algorithm is used to solve the cooperative multitask assignment model. By adjusting the weight, we can adapt to different battlefield environment and optimize the two index functions. Simulation results show the effectiveness of the proposed method.
【作者單位】： 海軍航空工程學(xué)院;
【基金】：航空基金(20135184007)
【分類號】：TP18;V279

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1 姜勝;陳啟卷;肖志懷;;一種基于矛盾思想方法的性能指標(biāo)函數(shù)[J];武漢大學(xué)學(xué)報(bào)(工學(xué)版);2010年02期

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本文編號：2090962