A Comprehensive Analysis of Parallel Genetic Algorithms

Abstract

The paper introduces an optimal approach for optimizing the idle time of processors through the utilization of parallel genetic algorithms. By harnessing the power of parallelism, we propose a method that effectively minimizes idle periods in processor operations. Our approach, outlined in detail within this paper, demonstrates significant improvements in resource utilization and efficiency. Through rigorous experimentation and analysis, we illustrate the efficacy of our parallel genetic algorithm in optimizing processor idle time. The findings presented herein offer promising insights into enhancing computational resource utilization, particularly in multi-processor systems. This research contributes to the ongoing efforts in maximizing computational efficiency and lays a foundation for further advancements in parallel optimization techniques. Keywords: Optimization; Metaheuristic; Parallel Genetic algorithm; Crossover; Mutation; Selection; Evolution;