The impact of a new formulation when solving the set covering problem using the ACO metaheuristic
Autor
Crawford B.
Soto R.
Palma W.
Paredes F.
Johnson F.
Norero E.
Resumen
The Set Covering Problem (SCP) is a well-known NP hard discrete optimization problem that has been applied to a wide range of industrial applications, including those involving scheduling, production planning and location problems. The main difficulties when solving the SCP with a metaheuristic approach are the solution infeasibility and set redundancy. In this paper we evaluate a state of the art new formulation of the SCP which eliminates the need to address the infeasibility and set redundancy issues. The experimental results, conducted on a portfolio of SCPs from the Beasley’s OR-Library, show the gains obtained when using a new formulation to solve the SCP using the ACO metaheuristic. © Springer International Publishing Switzerland 2015.
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