Abstract
We develop a modified hybrid sequential Lagrangean heuristic for the p-median problem and its shared memory parallel implementation using the OpenMP interface. The algorithm is based on finding the sequences of lower and upper bounds for the optimal value by use of a Lagrangean relaxation method with a subgradient column generation and a core selection approach in combination with a simulated annealing. The parallel algorithm is implemented using the shared memory (OpenMP) technology. The algorithm is then tested and compared with the most effective modern methods on a set of test instances taken from the literature.
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The work of A. Ushakov is supported by the Russian Science Foundation under grant 17-71-10176.
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Vasilyev, I., Ushakov, A. (2017). A Shared Memory Parallel Heuristic Algorithm for the Large-Scale p-Median Problem. In: Sforza, A., Sterle, C. (eds) Optimization and Decision Science: Methodologies and Applications. ODS 2017. Springer Proceedings in Mathematics & Statistics, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-67308-0_30
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