Creator:
Bell, Nathan John
Date:
2014
Abstract:
Particle Swarm Optimization (PSO) is a popular meta-heuristic for black-box optimization. Many variations and extensions of PSO have been developed since its creation in 1995, and the algorithm remains a popular topic of research. In this work we explore a new, abstracted, perspective of the PSO system and present the novel Particle Field Optimization (PFO) algorithm which harnesses this new perspective to achieve a behaviour distinct from traditional PSO systems.
Subject:
Computer Science
Language:
English
Publisher:
Carleton University
Identifier:
Thesis Degree Name:
Master of Computer Science:
M.C.S.
Thesis Degree Level:
Master's
Thesis Degree Discipline:
Computer Science
Parent Collection:
Theses and Dissertations