Improved Genetic Algorithm (IGA): Definition, Applications, and Enhancements

Improved Genetic Algorithm ('IGA') is a metaheuristic optimization algorithm that mimics the process of natural selection and evolution to find optimal solutions. It is an extension of the traditional Genetic Algorithm ('GA') that incorporates various modifications and enhancements to improve its performance and efficiency.

Some possible ways to describe IGA in a research paper are:

• In this study, we propose an Improved Genetic Algorithm ('IGA') that incorporates [list modifications/enhancements]. The proposed algorithm is compared with the traditional GA and other state-of-the-art algorithms on [list benchmark problems]. The experimental results show that IGA achieves [list advantages] in terms of [list performance metrics].
• To address the limitations of the traditional Genetic Algorithm ('GA'), we introduce an Improved Genetic Algorithm ('IGA') that [list modifications/enhancements]. The proposed algorithm is evaluated on [list real-world problems or applications], and the results demonstrate its effectiveness in [list benefits].
• Our work focuses on enhancing the performance of Genetic Algorithm ('GA') by introducing several improvements that collectively form the Improved Genetic Algorithm ('IGA'). The key modifications include [list details], which aim to [list objectives]. We evaluate IGA on [list synthetic or real-world problems], and the results show that it outperforms GA in terms of [list criteria].

The abbreviation for Improved Genetic Algorithm can be either IGA or IMPGA.