Abstract
In this paper a memetic algorithm integrating genetic procedures and local search, able to solve capacitated and uncapacitated dynamic location problems, is described. These problems are characterized by explicitly considering the possibility of a facility being opened, closed and reopened more than once during the planning horizon. It is also possible to explicitly consider different open and reopen fixed costs. The problems can be of single or multi-level nature. The computational results obtained show that the algorithm is capable of finding good quality solutions, but at the cost of large computational times, when compared with dedicated primal-dual heuristics and even with a general solver. Some changes are proposed to tackle this disadvantage.
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Dias, J., Captivo, M.E., Clímaco, J. (2007). A Memetic Algorithm for Dynamic Location Problems. In: Doerner, K.F., Gendreau, M., Greistorfer, P., Gutjahr, W., Hartl, R.F., Reimann, M. (eds) Metaheuristics. Operations Research/Computer Science Interfaces Series, vol 39. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71921-4_12
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DOI: https://doi.org/10.1007/978-0-387-71921-4_12
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