An algorithmic framework of discrete particle swarm optimization

Authors:
Jin Qin;Xin Li;Yixin Yin
Affiliations:
College of Computer Science & Information, Guizhou University, Guiyang 550025, China and College of Information Engineering, University of Science & Technology Beijing, Beijing 100083, China;College of Information Science & Engineering, Henan University of Technology, Zhengzhou 450052, China and College of Information Engineering, University of Science & Technology Beijing, Beijing 10 ...;College of Information Engineering, University of Science & Technology Beijing, Beijing 100083, China
Venue:
Applied Soft Computing
Year:
2012

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Abstract

Particle swarm optimization (PSO) was originally developed for continuous problem. To apply PSO to a discrete problem, the standard arithmetic operators of PSO are required to be redefined over discrete space. In this paper, a concept of distance over discrete solution space is introduced. Under this notion of distance, the PSO operators are redefined. After reinterpreting the composition of velocity of a particle, a general framework of discrete PSO algorithm is proposed. As a case study, we illustrate the application of the proposed discrete PSO algorithm to number partitioning problem (NPP) step by step. Preliminary computational experience is also presented. The successful application shows that the proposed algorithmic framework is feasible.