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Evolutionary Algorithms Approach for Cutting Stock Problem

References [1] C. Nitsche, G. Scheithauer, J. Terno, Tighter relaxations for the cutting stock problem, European Journal of Operational Research, No. 112, pp. 654-663, 1999 [2] T.H. Cormen , C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms, Second Edition, The Massachusetts Institute of Technology, 2001 [3] S.J. Russel, P. Norvig, Artificial Intelligence, A Modern Approach, Second Edition, Pearson Education, 2003 [4] M. Melanie, An Introduction to Genetic Algorithms, The

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Uncertainty-tolerant scheduling strategies for grid computing: knowledge-based techniques with bio-inspired learning

scheduling problems, Metaheuristics for Scheduling: Distributed Computing Environments, Studies in Computational Intelligence, pp. 1-37, 2008 [12] O. Cordon, F. Herrera, F. Hoffmann, L. Magdalena, Genetic fuzzy systems: Evolutionary tuning and learning of fuzzy knowledge bases,World Scientiffic Pub Co Inc, 2001 [13] C. Franke, F. Hoffmann, J. Lepping, U. Schwiegelshohn, Development of scheduling strategies with Genetic Fuzzy systems, Appl. Soft Comput, pp. 706-721, 2008 [14] S. Garcia-Galan, R.P. Prado, J.E. Munoz

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Shortest Path Problem Solving Based on Ant Colony Optimization Metaheuristic

References [1] M. Dorigo, Optimization, Learning and Natural Algorithms, Ph.D. Thesis, Politecnico di Milano, 1992. [2] M. Dorigo and T. Stützle, Ant Colony Optimization, The MIT Press, Cambridge, 2004. [3] M. Dorigo, V. Maniezzo and A. Colorni, The Ant System: Optimization by a colony of cooperating agents, in IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26(1):29-41, 1996. [4] T. Stützle and H. H. Hoos, The MAX-MIN Ant System and Local Search for the Traveling Salesman

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Processing Astronomical Image Mosaic Workflows With An Expert Broker In Cloud Computing

References [1] Belarbi, K., Titel, F., Bourebia, W., Benmahammed, K. (2005). Design of mamdani fuzzy logic controllers with rule base minimisation using genetic algorithm, Engineering Applications of Artificial Intelligence , 18(7), 875–880 [2] Bharathi, S., Chervenak, A., Deelman, E., Mehta, G., Su, M.-H., Vahi, K. (2008). Characterization of scientific workflows, in Workflows in Support of Large-Scale Science, 2008. WORKS 2008. Third Workshop on , 1–10 [3] Blythe, J., Jain, S., Deelman, E., Gil, Y., Vahi, K., Mandal, A., Kennedy, K. (2005

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Geographic Dijkstra-Based Multicast Algorithm for Wireless Sensor Networks

References [1] C. Garrozi and A. Araujo, Multiobjective Generic Algorithm for Multicast Routing, in Proc. of IEEE Congress on Evolutionary Computation, Vancouver, BC, Canada, July 2006, pp. 2513-2520. [2] B. Musznicki, M. Tomczak and P. Zwierzykowski, Dijkstra-based Localized Multicast Routing in Wireless Sensor Networks, in Proc. of CSNDSP 2012, 8th IEEE, IET Int. Symposium on Communication Systems, Networks and Digital Signal Processing, Pozna´n, Poland, Aug. 2012. [3] B. Musznicki and P. Zwierzykowski

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