Improved Information Sharing Mechanism (I2SM) for Metaheuristic Efficiency: A PSO Case Study

Abstract

This paper introduces a novel information sharing mechanism, the Improved Information Sharing Mechanism (I2SM), an adaptive real-time framework designed to enhance the performance of metaheuristic algorithms. I2SM dynamically collects and evaluates critical metrics, such as improvement rates and stagnation levels, through parallel processing, enabling real-time actions such as hybridization and parameter tuning. The mechanism’s adaptive nature ensures efficient handling of diverse optimization challenges by dynamically balancing exploration and exploitation, with a reasonable tradeoff in execution time.To assess the performance of the proposed I2SM mechanism, we selected the Particle Swarm Optimization (PSO) algorithm as a representative test framework. Empirical results from various benchmark functions demonstrate that PSO integrated with I2SM achieves superior performance, outperforming standard PSO in 90% of the cases. Although I2SM-PSO incurs a slightly higher execution time compared to standard PSO, significant improvements in solution quality validate its efficiency. However, this increase in execution time highlights a limitation that should be addressed in future research to optimize computational efficiency while maintaining performance gains.