Bio-Inspired Modifications of the PSO Algorithm
Melissa Cannas
Bio-Inspired Modifications of the PSO Algorithm.
Rel. Marco Scianna. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2023
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Abstract
In PSO, a population of individuals, referred to as "particles", move through the search space, adjusting their positions and velocities based on both their individual experiences and the experiences of the swarm as a whole. This combination of individual exploration and swarm cooperation helps guide the particles towards optimal solutions. This algorithm has several advantages: it is easy to describe and implement, requires a relatively small number of function evaluations to converge, and boasts a fast rate of convergence. It has undergone numerous variations and improvements, including modifications to the update equations, incorporation of constraints, and hybridization with other optimization techniques.
In this thesis, we will introduce bio-inspired modifications to the PSO algorithms, follow- ing the considerations given in Section 1.3
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