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The Impact of a New Formulation When Solving the Set Covering Problem Using the ACO Metaheuristic

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Modelling, Computation and Optimization in Information Systems and Management Sciences

Abstract

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.

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Correspondence to Broderick Crawford .

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Crawford, B., Soto, R., Palma, W., Paredes, F., Johnson, F., Norero, E. (2015). The Impact of a New Formulation When Solving the Set Covering Problem Using the ACO Metaheuristic. In: Le Thi, H., Pham Dinh, T., Nguyen, N. (eds) Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 360. Springer, Cham. https://doi.org/10.1007/978-3-319-18167-7_19

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  • DOI: https://doi.org/10.1007/978-3-319-18167-7_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18166-0

  • Online ISBN: 978-3-319-18167-7

  • eBook Packages: EngineeringEngineering (R0)

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