Computing Connected Resolvability of Graphs Using Binary Enhanced Harris Hawks Optimization

In this paper, we consider the NP-hard problem of finding minimum connected resolving set graphs. A vertex B a graph G resolves if every is uniquely identified by its vector distances to vertices in B. subgraph induced nontrivial G. The cardinality minimal metric dimension and solved heuristically binary version an enhanced Harris Hawk Optimization (BEHHO) algorithm. This first attempt determine heuristically. BEHHO combines classical HHO with opposition-based learning, chaotic local search equipped S-shaped transfer function convert continuous variable into one. hawks are encoded used represent which one belongs set. feasibility enforced repairing such that additional node selected from V\B added up obtain proposed algorithm compared (BHHO), learning (BOHHO), (BCHHO) algorithms. Computational results confirm superiority for determining dimension.