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Allende, H., Bravo, D., & Canessa, E. (2010). Robust design in multivariate systems using genetic algorithms. Qual. Quant., 44(2), 315–332.
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Alvarez-Miranda, E., & Pereira, J. (2017). Designing and constructing networks under uncertainty in the construction stage: Definition and exact algorithmic approach. Comput. Oper. Res., 81, 178–191.
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Alvarez-Miranda, E., Pereira, J., Torrez-Meruvia H., & Vila, M. (2021). A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations. Mathematics, 9(17), 2157.
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Araujo, J., Ducoffe, G., Nisse, N., & Suchan, K. (2018). On interval number in cycle convexity. Discret. Math. Theor. Comput. Sci., 20(1), 35 pp.
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Barrera, J., Moreno, E., & Varas, S. (2020). A decomposition algorithm for computing income taxes with pass-through entities and its application to the Chilean case. Ann. Oper. Res., 286(1-2), 545–557.
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Borquez-Paredes, D., Beghelli, A., Leiva, A., & Murrugarra, R. (2018). Does fragmentation avoidance improve the performance of dynamic spectrum allocation in elastic optical networks? Photonic Netw. Commun., 35(3), 287–299.
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Canessa, E., & Chaigneau, S. (2015). Calibrating Agent-Based Models Using a Genetic Algorithm. Stud. Inform. Control, 24(1), 79–90.
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Canessa, E., & Chaigneau, S. (2017). Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design. Ing. Invest., 37(2), 89–98.
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Canessa, E., Droop, C., & Allende, H. (2012). An improved genetic algorithm for robust design in multivariate systems. Qual. Quant., 46(2), 665–678.
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Canessa, E., Vera, S., & Allende, H. (2012). A new method for estimating missing values for a genetic algorithm used in robust design. Eng. Optimiz., 44(7), 787–800.
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Carrasco, R. A., Iyengar, G., & Stein, C. (2018). Resource cost aware scheduling. Eur. J. Oper. Res., 269(2), 621–632.
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Celis, P., de la Cruz, R., Fuentes, C., & Gomez, H. W. (2021). Survival and Reliability Analysis with an Epsilon-Positive Family of Distributions with Applications. Symmetry, 13(5), 908.
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Dumett, M. A., & Cominetti, R. (2018). On The Stability Of An Adaptive Learning Dynamics In Traffic Games. J. Dyn. Games, 5(4), 265–282.
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Fernandez, C., Valle, C., Saravia, F., & Allende, H. (2012). Behavior analysis of neural network ensemble algorithm on a virtual machine cluster. Neural Comput. Appl., 21(3), 535–542.
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Feuilloley, L., Fraigniaud, P., Montealegre, P., Rapaport, I., Remila, E., & Todinca, I. (2021). Compact Distributed Certification of Planar Graphs. Algorithmica, Early Access.
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Goles, E., & Montealegre, P. (2020). The complexity of the asynchronous prediction of the majority automata. Inf. Comput., 274(SI).
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Goles, E., Maldonado, D., Montealegre, P., & Ollinger, N. (2020). On the complexity of the stability problem of binary freezing totalistic cellular automata. Inf. Comput., 274, 21 pp.
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Henriquez, P. A., & Ruz, G. A. (2018). A non-iterative method for pruning hidden neurons in neural networks with random weights. Appl. Soft. Comput., 70, 1109–1121.
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Jenkins, J. S., Diaz, M. R., Kurtovic, N. T., Espinoza, N., Vines, J. I., Rojas, P. A. P., et al. (2020). An ultrahot Neptune in the Neptune desert. Nat. Astron., 4(12), 1148–1157.
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Lagos, T., Armstrong, M., Homem-de-Mello, T., Lagos, G., & Saure, D. (2021). A framework for adaptive open-pit mining planning under geological uncertainty. Optim. Eng., 72, 102086.
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