本文選題：直覺(jué)模糊集 + 小生境�。� 參考：《計(jì)算機(jī)科學(xué)》2016年12期

【摘要】：提出一種基于直覺(jué)模糊距離測(cè)度的小生境技術(shù),結(jié)合模糊控制的自適應(yīng)遺傳算法求解旅行商問(wèn)題。運(yùn)用個(gè)體在遺傳算法迭代尋優(yōu)中的適應(yīng)度值,通過(guò)直覺(jué)模糊集的距離測(cè)度確定個(gè)體之間的相似性,使用共享函數(shù)和懲罰函數(shù)對(duì)適應(yīng)度低的個(gè)體進(jìn)行懲罰和淘汰,維護(hù)了種群個(gè)體的多樣性;建立模糊推理系統(tǒng),以自適應(yīng)調(diào)節(jié)遺傳算法迭代中的交叉率和變異率,使遺傳算法能在局部尋優(yōu)和全局尋優(yōu)之間達(dá)到平衡,彌補(bǔ)遺傳算法易早熟收斂和后期尋優(yōu)能力差的缺陷;通過(guò)求解TSPLIB中的多組實(shí)例并進(jìn)行對(duì)比,結(jié)果表明所提算法的收斂速度、優(yōu)化精度、效率均具有明顯優(yōu)勢(shì)。
[Abstract]:A niche technology based on intuitionistic fuzzy distance measure is proposed, which combines the adaptive genetic algorithm of fuzzy control to solve the traveling salesman problem. By using the fitness value of the individual in the genetic algorithm iterative optimization, the similarity between individuals is determined by the distance measure of the intuitionistic fuzzy set, and the fitness is low by using the shared function and the penalty function. The individual is punished and eliminated, and the diversity of the individual is maintained, and a fuzzy inference system is established to adjust the cross rate and mutation rate in the iteration of the genetic algorithm, so that the genetic algorithm can balance between the local optimization and the global optimization, and make up the defects of the early convergence and the poor optimization ability of the genetic algorithm. Several examples of TSPLIB are compared and the results show that the proposed algorithm has obvious advantages in terms of convergence speed, optimization accuracy and efficiency.

【作者單位】： 空軍工程大學(xué)防空反導(dǎo)學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(61402517) 中國(guó)博士后基金(2013M542331) 陜西省自然科學(xué)基金(2013JQ8035)資助
【分類號(hào)】：TP18

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本文編號(hào)：1792013