ABSTRACT The genetic algorithm (GA) is one of the most common solutions to solve many optimisation problems. Its distributed version, Island Model GA (IMGA), was introduced to overcome more complex and scalable cases. However, there is a recurrent problem in IMGA called premature convergence as a consequence of selection in the migration. This process is a mechanism of migrating individuals from one into another island to keep population diversity. The primary cause is the structural similarity of a migrated individual because of the genetic operator configurations are identical. Localised IMGA (LIMGA) tries to implement different island characteristics to avoid premature convergence. The main motivation of this paper is to investigate the performance of LIMGA capability in maintaining population diversity. In detail, the contributions of this research are (1) to prove LIMGA concept in handling general optimisation problem, (2) to analyse the performance LIMGA in diversity preservation, and (3) compare LIMGA performance with the current solvers. By harmonising three different GA cores, LIMGA could overcome computationally expensive functions with a great result and acceptable execution time. Moreover, because of its success in maintaining the diversity, Localised Island Model Genetic Algorithm (LIMGA) could lead to the among other current solvers for this case.

中文翻译：

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岛屿模型遗传算法在种群多样性保护中的定位策略性能分析

摘要 遗传算法（GA）是解决许多优化问题的最常见的解决方案之一。其分布式版本 Island Model GA (IMGA) 被引入以克服更复杂和可扩展的情况。但是，由于迁移中的选择，IMGA 中存在一个反复出现的问题，称为过早收敛。这个过程是一种将个体从一个岛屿迁移到另一个岛屿以保持种群多样性的机制。主要原因是迁移个体的结构相似，因为遗传算子配置相同。Localized IMGA (LIMGA) 尝试实现不同的岛屿特征以避免过早收敛。本文的主要动机是研究 LIMGA 能力在维持种群多样性方面的表现。详细，本研究的贡献是 (1) 证明 LIMGA 概念在处理一般优化问题方面，(2) 分析 LIMGA 在多样性保持方面的性能，以及 (3) 将 LIMGA 性能与当前求解器进行比较。通过协调三个不同的 GA 内核，LIMGA 可以克服计算成本高的函数，并获得良好的结果和可接受的执行时间。此外，由于其在保持多样性方面的成功，局部岛模型遗传算法 (LIMGA) 可能会导致其他当前解决方案中的这种情况。LIMGA 可以克服计算成本高的函数，并具有良好的结果和可接受的执行时间。此外，由于其在保持多样性方面的成功，局部岛模型遗传算法 (LIMGA) 可能会导致其他当前解决方案中的这种情况。LIMGA 可以克服计算成本高的函数，并具有良好的结果和可接受的执行时间。此外，由于其在保持多样性方面的成功，局部岛模型遗传算法 (LIMGA) 可能会导致其他当前解决方案中的这种情况。