A Hybrid Particle Swarm Branch-and-Bound (HPB) Optimizer for Mixed Discrete Nonlinear Programming

This paper proposes a new algorithm for solving mixed discrete nonlinear programming (MDNLP) problems, designed to efficiently combine particle swarm optimization (PSO), which is a well-known global optimization technique, and branch-and-bound (BB), which is a widely used systematic deterministic al...

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Bibliographic Details

Published in:	IEEE transactions on systems, man and cybernetics. Part A, Systems and humans Vol. 38; no. 6; pp. 1411 - 1424
Main Authors:	Nema, S., Goulermas, J., Sparrow, G., Cook, P.
Format:	Journal Article
Language:	English
Published:	IEEE 01.11.2008
Subjects:	Algorithm design and analysis Branch-and-bound (BB) Computer architecture Constraint optimization Design optimization Functional programming hybridization Mathematical programming mixed discrete nonlinear programming (MDNLP) Optimization methods Particle swarm optimization particle swarm optimization (PSO) Quadratic programming Stochastic processes
ISSN:	1083-4427, 1558-2426
Online Access:	Get full text
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