Computing the Metric Dimension of Hypercube Graphs by Particle Swarm Optimization Algorithms
Danang Triantoro Murdiansyah, Adiwijaya Adiwijaya · Advances in intelligent systems and computing · 2016
In this paper, we present a PSO (Particle Swarm Optimization) algorithm for determining the metric dimension of graphs. We choose PSO because of its simplicity, robustness, and adaptability for various optimization problems [ 5 ]. Our PSO uses the binary valued vector for particles. The binary valued vector is used to represent which one of vertices of a graph is belong to resolving set. The feasibility is enforced by repairing particles. We tested our PSO by computing the metric dimension of hypercube graphs. The result is our PSO can achieve metric dimension known in literature [ 8 ] in reasonable amount of time.