Two‐phase strategies for the bi‐objective minimum spanning tree problem

This paper presents a new two-phase algorithm for the bi-objective minimum spanning tree (BMST) problem. In first phase, it computes extreme supported efficient solutions resorting to both mathematical programming and algorithmic approaches, while second phase is devoted obtaining remaining (non-extreme non-supported). latter based on recursive procedure capable of generating all trees connected graph through edge interchanges increasing evaluation non-zero reduced costs associated weighted linear programs. Such exploits common property wider class problems which (MST) problem belongs, that structure its basic feasible solutions. Computational experiments are conducted different families graphs with types cost. These results show this correct, very easy implement allows one extract conclusions difficulty finding entire set Pareto BMST depending topology possible correlation costs.