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

In this paper, an optimisation technique based on the Particle Swarm Optimization (PSO) algorithm will be experimented upon the Multi-dimensional Knapsack Problem. Through the merging of fundamental concepts of the existing PSO algorithm and selected features of evolutionary 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 algorithm 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.