Abstract
We experimentally compare synchronous and asynchronous parallelization of the SMS-EMOA. We find that asynchronous parallelization usually obtains a better speed-up and is more robust to fluctuations in the evaluation time of objective functions. Simultaneously, the solution quality of both methods only degrades slightly as against the sequential variant. We even consider it possible for the parallelization to improve the quality of the solution set on some multimodal problems.
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With a runnable example in the documentation at https://ls11-www.cs.tu-dortmund.de/people/swessing/evoalgos/doc/algo.html.
References
Beume, N., Naujoks, B., Emmerich, M.: SMS-EMOA: multiobjective selection based on dominated hypervolume. Eur. J. Oper. Res. 181(3), 1653–1669 (2007)
Bringmann, K., Friedrich, T.: Don’t be greedy when calculating hypervolume contributions. In: Proceedings of the Tenth ACM SIGEVO Workshop on Foundations of Genetic Algorithms, FOGA 2009, pp. 103–112. ACM (2009)
Depolli, M., Trobec, R., Filipič, B.: Asynchronous master-slave parallelization of differential evolution for multi-objective optimization. Evol. Comput. 21(2), 261–291 (2012)
Huband, S., Hingston, P., Barone, L., While, L.: A review of multiobjective test problems and a scalable test problem toolkit. IEEE Trans. Evol. Comput. 10(5), 477–506 (2006)
Klinkenberg, J.W., Emmerich, M.T.M., Deutz, A.H., Shir, O.M., Bäck, T.: A reduced-cost SMS-EMOA using kriging, self-adaptation, and parallelization. In: Ehrgott, M., Naujoks, B., Stewart, J.T., Wallenius, J. (eds.) Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems. Lecture Notes in Economics and Mathematical Systems, vol. 634, pp. 301–311. Springer, Heidelberg (2010)
Märtens, M., Izzo, D.: The asynchronous island model and NSGA-II: study of a new migration operator and its performance. In: Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013, pp. 1173–1180. ACM (2013)
Menges, D.A., Wessing, S., Rudolph, G.: Asynchrone Parallelisierung des SMS-EMOA zur Parameteroptimierung von mobilen Robotern. In: Hoffmann, F., Hüllermeier, E. (eds.) Proceedings 25, Workshop Computational Intelligence. Schriftenreihe des Instituts für Angewandte Informatik/Automatisierungstechnik, vol. 54, pp. 47–65. KIT Scientific Publishing (2015). (in German)
Schütze, O., Esquivel, X., Lara, A., Coello Coello, C.A.: Using the averaged Hausdorff distance as a performance measure in evolutionary multiobjective optimization. IEEE Trans. Evol. Comput. 16(4), 504–522 (2012)
Wessing, S.: evoalgos: modular evolutionary algorithms (2016). Python package version 0.3. https://pypi.python.org/pypi/evoalgos
Wessing, S.: optproblems: infrastructure to define optimization problems and some test problems for black-box optimization (2016). Python package version 0.8. https://pypi.python.org/pypi/optproblems
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Wessing, S., Rudolph, G., Menges, D.A. (2016). Comparing Asynchronous and Synchronous Parallelization of the SMS-EMOA. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_52
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