Abstract
In the future smart city, citizens are interconnected and easily share information anywhere, anytime. Through a sensor network integrated with real time monitoring systems, data are collected, processed and analyzed. Of course, this is already happening, in part. Nowdays, the number of portable devices that are available to all people is huge and we can find them everywhere, they are not only smartphones but also tablets, IoT, and other. This is a perfect scenario to start new lines of research on the actual suitability of portable devices to solve real optimization and machine learning problems. On the one hand, the fact that they are everywhere encourages research aimed at their collaboration in a distributed way. On the other hand, genetic algorithms are metaheuristics where parallelization takes on great importance. In this paper, we analyze the numerical behavior of distributed genetic algorithms on portable devices. We focus on the behavior of the distributed algorithm when we modify the number of interconnected devices, as well as the behavior of the algorithm when the devices with different performances collaborate together. As a conclusion, the numerical results support the future research in the concept of distributed intelligence everywhere, since algorithms worked out accurate and efficient results.
This research has been partially funded by I Plan Propio de Investigacón y Transferencia de la Universidad de Málaga 2016–2017. Also, partially funded by the Spanish MINECO project TIN2014-57341-R (http://moveon.lcc.uma.es).
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Alba, E., Blum, C., Asasi, P., Leon, C., Gomez, J.A.: Optimization Techniques for Solving Complex Problems, vol. 76. Wiley, Hoboken (2009)
Bäck, T., Fogel, D.B., Michalewicz, Z.: Handbook of Evolutionary Computation. Oxford, New York (1997)
Michaelwicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer, Heidelberg (1992)
Alba, E., Tomassini, M.: Parallelism and evolutionary algorithms. IEEE Trans. Evol. Comput. 6(5), 443–462 (2002)
Letchford, A.N., Lysgaard, J., Eglese, R.W.: A branch-and-cut algorithm for the capacitated open vehicle routing problem. J. Oper. Res. Soc. 58(12), 1642–1651 (2007)
Wassan, N.A., Wassan, A.H., Nagy, G.: A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries. J. Comb. Optim. 15(4), 368–386 (2008)
Dantzig, G.B., Ramser, J.H.: The truck dispatching problem. Manage. Sci. 6(1), 80–91 (1959)
Gary, M.R., Johnson, D.S.: Computers and intractability: a guide to the theory of NP-completeness (1979)
Alba, E., Dorronsoro, B.: Solving the vehicle routing problem by using cellular genetic algorithms. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2004. LNCS, vol. 3004, pp. 11–20. Springer, Heidelberg (2004). doi:10.1007/978-3-540-24652-7_2
Alba, E., Dorronsoro, B.: Cellular Genetic Algorithms, vol. 42. Springer Science & Business Media, New York (2009)
Alba, E., Dorronsoro, B.: Computing nine new best-so-far solutions for capacitated vrp with a cellular genetic algorithm. Inf. Process. Lett. 98(6), 225–230 (2006)
Cintrano, C., Alba, E.: Genetic algorithms running into portable devices: a first approach. In: Luaces, O., Gámez, J.A., Barrenechea, E., Troncoso, A., Galar, M., Quintián, H., Corchado, E. (eds.) CAEPIA 2016. LNCS, vol. 9868, pp. 383–393. Springer, Cham (2016). doi:10.1007/978-3-319-44636-3_36
Christofides, N.: Combinatorial optimization. In: Nicos, C. (ed.) A Wiley-Interscience Publication, Based on a series of lectures, given at the Summer School in Combinatorial Optimization, held in Sogesta, Italy, 30 May - 11 June 1977. Wiley, Chichester (1979)
Nesmachnow, S., Cancela, H., Alba, E.: Heterogeneous computing scheduling with evolutionary algorithms. Soft. Comput. 15(4), 685–701 (2010)
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Morell, J.A., Alba, E. (2017). Distributed Genetic Algorithms on Portable Devices for Smart Cities. In: Alba, E., Chicano, F., Luque, G. (eds) Smart Cities. Smart-CT 2017. Lecture Notes in Computer Science(), vol 10268. Springer, Cham. https://doi.org/10.1007/978-3-319-59513-9_6
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DOI: https://doi.org/10.1007/978-3-319-59513-9_6
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