Digital Library

of the European Council for Modelling and Simulation



Solving A Multi-Dimensional Knapsack Problem Using A Hybrid Particle Swarm Optimization Algorithm


Nam Fai Wan, Lars Nolle

Published in:


ECMS 2009 Proceedings

Edited by: Javier Otamendi, Andrzej Bargiela, Jose Luis Montes, L.M.D. Pedrera


ISBN: 978-0-9553018-8-9

Doi: 10.7148/2009


23rd European Conference on Modelling and Simulation,

Madrid, June 9-12, 2009

Citation format:

Lee, L. W., & Bargiela, A. (2010). Statistical Extraction Of Protein Surface Atoms Based On A Voxelisation Method. Simulation Meets Global Challenges (pp. 344-349). European Council for Modeling and Simulation.



In this paper, an optimisation technique based on the Par- ticle Swarm Optimization (PSO) algorithm will be ex- perimented upon the Multi-dimensional Knapsack Prob- lem. Through the merging of fundamental concepts of the existing PSO algorithm and selected features of evo- lutionary algorithms, a novel hybrid algorithm is created. When testing the algorithm against a test suite publicly available on OR-LIB, it was discovered that the algo- rithm is able to locate fitness values very close to best available results discovered using Linear Programming techniques, even though the algorithm is at the very early stage of development. Such an observation reveals the potential of this algorithm, calling for further research to be made upon it.

Full text: