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首页> 外文会议>2011 International Conference on Mechatronic Science, Electric Engineering and Computer >An improve self-adaption NGA with predator
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An improve self-adaption NGA with predator

机译：具有捕食者的改进的自适应NGA

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摘要

Because have very high ability of overall situation searching and convergence speed, show excellently in keeping solution variety, the niche genetic algorithm(NGA) is widely used to solving various kinds of combination optimization problem, but the traditional niche genetic algorithm(T-GA) have the problem that the discrimination standard of Euclidean distance between two individuals is not development and change with algorithm's evolution process, and it unable to avoid the propagate of inferior solution when keep the variety of solution, so reduced the speed of convergence and operating greatly. To counter these questions, this paper has proposed an improved self-adaptation NGA with predator, in this algorithm, at first, improved the discrimination standard of Euclidean distance, make it can change with the evolution process; then introduce the concept of predator in the artificial life algorithm, settle predator to clear up and limit the propagate of inferior solution; Finally, through use this algorithm to solve the 0–1 knapsack questions, proved that the improvement of discrimination standard of Euclidean distance and the introduction of predator heighten the efficiency of algorithm greatly.
机译：由于整体情况的高能力搜索和收敛速度，出于保持解决方案品种的优势，利基遗传算法（NGA）广泛用于解决各种组合优化问题，而是传统的利基遗传算法（T-GA）有问题是，两个人之间的欧几里德距离的歧视标准并非开发和随算法的演化过程而变化，并且当保持各种解决方案时，它无法避免劣质解决方案，因此降低了收敛速度并大大降低了速度。为了抵消这些问题，本文提出了一种具有捕食者的改进的自适应NGA，在本算法中，首先改进了欧几里德距离的鉴别标准，使其可以随着演进过程而变化;然后在人工生命算法中介绍捕食者的概念，沉降捕食者清除并限制劣质溶液的传播;最后，通过使用该算法来解决0-1的背包问题，证明了欧几里德距离的鉴别标准的提高以及捕食者的引入大大提高了算法的效率。

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