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Updated: Jun 24, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Comparative assessment of differently randomized accelerated particle swarm optimization and squirrel search
Muhammad Ayyaz Tariq1, Muhammad Salman Fakhar2, Ghulam Abbas3
1Department of Electrical Engineering, University of Engineering and Technology, Lahore, 54890, Pakistan. ayyaztariq@hotmail.com.
Abstract:
A random initialization of the search particles is a strong argument in favor of the deployment of nature-inspired metaheuristic algorithms when the knowledge of a good initial guess is lacked. This article analyses the impact of the type of randomization on the working of algorithms and the acquired solutions. In this study, five different types of randomizations are applied to the Accelerated Particle Swarm Optimization (APSO) and Squirrel Search Algorithm (SSA) during the initializations and proceedings of the search particles for selective harmonics elimination (SHE). The types of randomizations include exponential, normal, Rayleigh, uniform, and Weibull characteristics. The statistical analysis shows that the type of randomization does impact the working of optimization algorithms and the fittest value of the objective function.
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