Abstract
A planar competitive location and design problem with variable demand is considered. The assumption that the demand may vary depending on the conditions of the market makes the problem more realistic, but it also increases its complexity, and therefore, the computational effort needed to solve it. In this paper, a modification of a heuristic recently proposed to cope with the problem is presented, which allows, on the one hand, to obtain the same solutions as the original heuristic more quickly and, on the other hand, to handle larger size problems. Furthermore, a parallel version of the algorithm, suitable for being run in most of today’s personal computers, has also been proposed. The parallel algorithm has been implemented using the OpenMP library and the results show an ideal efficiency up to at least eight processors (the largest number of available processing elements). The effectiveness of the parallel algorithm has also been measured. From the computational results, it can be inferred that the proposed parallelization is robust.
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Agulleiro, J., Fernández, J.J.: Fast tomographic reconstruction on multicore computers. Bioinformatics 27(4), 582–583 (2011)
Agulleiro, J., Garzón, E., García, I., Fernández, J.J.: Vectorization with simd extensions speeds up reconstruction in electron tomography. J. Struct. Biol. 170(3), 570–575 (2010)
Berman, O., Krass, D.: Locating multiple competitive facilities: spatial interaction models with variable expenditures. Ann. Oper. Res. 111(1), 197–225 (2002)
Campbell, J., Stiehr, G., Ernst, A., Krishnamoorthy, M.: Solving hub arc location problems on a cluster of workstations. Parallel Comput. 29(5), 555–574 (2003)
Chapman, B., Jost, G., van der Pas, R.: Using OpenMP. Portable shared memory parallel programming. The MIT Press, Cambridge (2008)
Crainic, T., Toulouse, M., Gendreau, M.: Synchronous tabu search parallelization strategies for multicommodity location-allocation with balancing requirements. OR Spectr. 17(2–3), 113–123 (1995)
Crainic, T., Toulouse, M., Gendreau, M.: Parallel asynchronous tabu searh for multicomodity location-allocation with balancing requirements. Ann. Oper. Res. 63(2), 277–299 (1996)
Cura, T.: A parallel local search approach to solving the uncapacitated warehouse location problem. Comput. Ind. Eng. 59(4), 1000–1009 (2010)
Drezner, T., Drezner, Z., Salhi, S.: Solving the multiple competitive facilities location problem. Eur. J. Oper. Res. 142(1), 138–151 (2002)
Drezner, Z., Hamacher, H.: Facility Location. Applications and Theory. Springer, Berlin (2002)
Fernández, J., Pelegrín, B., Plastria, F., Tóth, B.: Solving a Huff-like competitive location and design model for profit maximization in the plane. Eur. J. Oper. Res. 179(3), 1274–1287 (2007)
Francis, R., McGinnis, L., White, J.: Facility Layout and Location: An Analytical Approach. Prentice Hall, Englewood Cliffs (1992)
García-López, F., Melián-Batista, B., Moreno-Pérez, J., Moreno-Vega, J.: The parallel variable neighborhood search for the \(p\)-median problem. J. Heuristics 8(3), 375–388 (2002)
Gendron, B., Crainic, T.: A parallel branch-and-bound algorithm for multicommodity location with balancing requirements. Comput. Oper. Res. 24(9), 829–847 (1997)
Hammer, R., Hocks, M., Kulisch, U., Ratz, D.: C++ Toolbox for Verified Computing I: Basic Numerical Problems: Theory, Algorithms, and Programs. Springer, Berlin (1995)
Hennessy, J., Patterson, D.: Computer Architecture, Fourth Edition: A Quantitative Approach. Morgan Kaufmann Publishers Inc., San Francisco (2006)
Knüppel, O.: PROFIL/BIAS—a fast interval library. Computing 1(53), 277–287 (1993)
Redondo, J., Fernández, J., Arrondo, A.G., García, I., Ortigosa, P.: Fixed or variable demand? Does it matter when locating a facility? Omega 40(1), 9–20 (2012)
Redondo, J., Fernández, J., García, I., Ortigosa, P.: Parallel algorithms for continuous competitive location problems. Optim. Methods Softw. 23(5), 779–791 (2008)
Redondo, J., Fernández, J., García, I., Ortigosa, P.: Parallel algorithms for multifacilities continuous competitive location problems. J. Global Optim. 50(4), 557–573 (2011)
Redondo, J., Fernández, J., García, I., Ortigosa, P.: Solving the facility location and design \((1|1)\)-centroid problem via parallel algorithms. J. Supercomput. 58(3), 420–428 (2011)
Redondo, J., García, I., Ortigosa, P., Pelegín, B., Fernández, P.: Parallelization of an algorithm for finding facility locations for an entering firm under delivered pricing. In: Proceedings of Parallel Computing, (PARCO 2005), pp. 269–276 (2005)
Rosen, J., Xue, G.L.: Computational comparison of two algorithms for the euclidean single facility location problem. ORSA J. Comput. 3(3), 207–212 (1991)
de Silva, A., Abramson, D.: A parallel interior point method and its application to facility location problems. Comput. Optim. Appl. 9(3), 249–273 (1998)
Tóth, B., Fernández, J.: Interval Methods for Single and Bi-objective Optimization Problems—Applied to Competitive Facility Location Models. Lambert Academic Publishing, Saarbrücken (2010)
Tóth, B., Plastria, F., Fernández, J., Pelegrín, B.: On the impact of spatial pattern, aggregation, and model parameters in planar Huff-like competitive location and design problems. OR Spectr. 31(3), 601–627 (2009)
Weiszfeld, E.: Sur le point pour lequel la somme des distances de \(n\) points donnés est minimum. Tohoku Math. J. 43, 355–386 (1937)
Wesolowsky, G.: The Weber problem: history and perspectives. Location Sci. 1(1), 5–23 (1993)
Acknowledgments
This work has been funded by grants from the Spanish Ministry of Science and Innovation (TIN2008-01117, ECO2011-24927), Junta de Andalucía (P08-TIC-3518 and P10-TIC-6002) and Fundación Séneca (The Agency of Science and Technology of the Region of Murcia, 00003/CS/10 and 15254/PI/10), in part financed by the European Regional Development Fund (ERDF). Juana López Redondo is a fellow of the Spanish ‘Juan de la Cierva’ contract program.
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Arrondo, A.G., Fernández, J., Redondo, J.L. et al. An approach for solving competitive location problems with variable demand using multicore systems. Optim Lett 8, 555–567 (2014). https://doi.org/10.1007/s11590-012-0596-z
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DOI: https://doi.org/10.1007/s11590-012-0596-z