A new quantum behaved particle swarm optimization

This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the characteristics of QPSO, and uses interpolation based recombination operator for generating a new solution vector in the search space. The performance of Q-QPSO is compared with Basic Particle Swarm Optimization (BPSO), QPSO and two other variants of QPSO taken from literature on six standard unconstrained, scalable benchmark problems. The experimental results show that the proposed algorithm outperforms the other algorithms quite significantly. Categories and Subject Descriptors D.3.3 [Programming Languages]: Language Contructs and – abstract data types, polymorphism General Terms Algorithms, Performance, Reliability, Experimentation Keywords Particle swarm optimization, Interpolation, Global optimization, Quantum behavior.

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Millie Pant, Radha Thangaraj, Ajith Abraham
• Keywords: GECCO 2008, Global Optimization, Optimization, Particle Swarm Optimization, Quantum Behaved Particle