An iterated greedy algorithm with variable reconstruction size for the obnoxious <i>p</i>‐median problem

The obnoxious p-median problem is a facility location where we maximise the sum of distances between each client point and its nearest facility. Since it nondeterministic polynomial-time (NP)-hard, most algorithms designed for follow metaheuristic strategies to find high-quality solutions in affordable time but with no optimality guarantee. In this paper, variant iterated greedy algorithm developed problem. It adopts idea increasing search radius used variable neighbourhood by number reconstructed components at iteration improved solution, amount increase determined dynamically based on quality current solution. We demonstrate that new significantly outperforms state-of-the-art standard datasets.