International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 169 - Number 5 |
Year of Publication: 2017 |
Authors: Eman Yassien, Raja Masadeh, Abdullah Alzaqebah, Ameen Shaheen |
10.5120/ijca2017914734 |
Eman Yassien, Raja Masadeh, Abdullah Alzaqebah, Ameen Shaheen . Grey Wolf Optimization Applied to the 0/1 Knapsack Problem. International Journal of Computer Applications. 169, 5 ( Jul 2017), 11-15. DOI=10.5120/ijca2017914734
The knapsack problem (01KP ) in networks is investigated in this paper. A novel algorithm is proposed in order to find the best solution that maximizes the total carried value without exceeding a known capacity using Grey Wolf Optimization (GWO) and K-means clustering algorithms. GWO is a recently established meta-heuristics for optimization, inspired by grey wolf's species. K-means clustering algorithm is used to group each 5-12 agents with each other at one cluster according to GWO constraint. The evaluated performance is satisfying. The simulation results show great compatibility between experimental and theoretical results.