Adaptive mutation in dynamic environments

Chigozirim J. Uzor, M. Gongora, S. Coupland, Benjamin N. Passow
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引用次数: 3

Abstract

The interest in nature inspired optimization in dynamic environments has been increasing constantly over the past years. This trend implies that many real world problems experience dynamic changes and it is important to develop an efficient algorithm capable of tackling these problems. Several techniques have been developed over the past two decades for solving dynamic optimization problems. Among these techniques, the hypermutation scheme has proved to be beneficial in solving some of the dynamic optimization problems but requires that the mutation factors be picked a priori. This paper investigates a new mutation and change detection scheme for compact genetic algorithm (cGA), where the degree of change regulates the mutation rate (i.e. mutation rate is directly proportional to the degree of change). The experimental results shows that the mutation and change detection scheme has an impact on the performance of the cGA in dynamic environments and that the effect of the proposed scheme depends on the dynamics of the environment.
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动态环境中的适应性突变
在过去的几年里,人们对自然激发的动态环境优化的兴趣一直在不断增加。这一趋势表明,许多现实世界的问题都会经历动态变化,因此开发一种能够解决这些问题的有效算法非常重要。在过去的二十年里,已经发展了几种解决动态优化问题的技术。在这些技术中,超突变方案已被证明有利于解决一些动态优化问题,但需要先验地选择突变因子。本文研究了紧凑遗传算法(cGA)的一种新的突变和变化检测方案,其中变化程度调节突变率(即突变率与变化程度成正比)。实验结果表明,突变和变化检测方案会影响动态环境下cGA的性能,并且所提出方案的效果取决于环境的动态性。
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