Partial reformulation-linearization based optimization models for the Golomb ruler problem

In this paper, we provide a straightforward proof of a conjecture proposed in [P. Duxbury, C. Lavor and L.L. de Salles-Neto, RAIRO:RO 55 (2021) 2241-2246.] regarding the optimal solutions of a non-convex mathematical programming model of the Golomb ruler problem. Subsequently, we investigate the computational efficiency of four new binary mixed-integer linear programming models to compute optimal Golomb rulers. These models are derived from a well-known nonlinear integer model proposed in [B. Kocuk and W.-J. van Hoeve, A Computational Comparison of Optimization Methods for the Golomb Ruler Problem. (2019) 409-425.], utilizing the reformulation-linearization technique. Finally, we provide the correct outputs of the greedy heuristic proposed in [P. Duxbury, C. Lavor and L.L. de Salles-Neto, RAIRO:RO 55 (2021) 2241-2246.] and correct false conclusions stated or implied therein.