Improved ant colony optimization algorithms for continuous ... - CoDE

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66 BIBLIOGRAPHY Proceedings of the 4th international conference on Hybrid metaheuristics, volume 4771 of LNCS, pages 108–122, Berlin, Germany, 2007. Springer. [10] G. Bilchev and I.C. Parmee. The ant colony metaphor for searching continuous design spaces. In Terence C. Fogarty, editor, Proceedings of the AISB Workshop on Evolutionary Computation, volume 993 of LNCS, pages 25–39. Springer-Verlag, Berlin, Germany, 1995. [11] M. Birattari. The Problem of Tuning Metaheuristics as Seen From a Machine Learning Perspective. PhD thesis, volume 292 of Dissertationen zur Künstlichen Intelligenz. Akademische Verlagsgesellschaft Aka GmbH, Berlin, Germany, 2005. [12] M. Birattari, T. Stützle, L. Paquete, and K. Varrentrapp. A racing algorithm for configuring metaheuristics. In W. B. Langdon et al., editor, Proceedings of the Genetic and Evolutionary Computation Conference, pages 11–18. Morgan Kaufman, San Francisco, CA, 2002. [13] M. Birattari, Z. Yuan, P. Balaprakash, and T. Stützle. F-Race and iterated F-Race: An overview. Experimental Methods for the Analysis of Optimization Algorithms, pages 311–336, 2010. [14] Christian Blum, M. Yábar Vallès, and María J. Blesa. An ant colony optimization algorithm for DNA sequencing by hybridization. Computers & Operations Research, 35(11):3620–3635, 2008. [15] Y.J. Cao and Q.H. Wu. Mechanical design optimization by mixedvariable evolutionary programming. In Proceedings of IEEE Conference on Evolutionary Computation, pages 443–446, Piscataway, NJ, 1997. IEEE Press. [16] J.L. Chen and Y.C. Tsao. Optimal design of machine elements using genetic algorithms. CHUNG-KUO CHI HSUEH KUNG CH’ENG HSUEH PAO., 14(2):193–199, 1993. [17] C. Coello and A. Carlos. Use of a self-adaptive penalty approach for engineering optimization problems. Computers in Industry, 41(2):113– 127, 2000. [18] C.A.C. Coello and R.L. Becerra. Efficient evolutionary optimization through the use of a cultural algorithm. Engineering Optimization, 36(2):219–236, 2004. [19] C.A. Coello Coello and E. Mezura Montes. Constraint-handling in genetic algorithms through the use of dominance-based tournament selection. Advanced Engineering Informatics, 16(3):193–203, 2002.
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Université Libre de Bruxelles Facu
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Acknowledgements I thank Prof. Marc
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Contents Abstract iii Acknowledgeme
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Chapter 1 Introduction Metaheuristi
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them in the smallest function evalu
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6 Ant Colony Optimization Algorithm
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8 Ant Colony Optimization Algorithm
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10 Ant Colony Optimization of Sep-A
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12 Ant Colony Optimization Average
Page 25 and 26: Chapter 3 An Incremental Ant Colony
Page 27 and 28: 3.2 IACOR with Local Search 17 3.2
Page 29 and 30: 3.3 Experimental Study 19 Algorithm
Page 31 and 32: 3.3 Experimental Study 21 Table 3.2
Page 33 and 34: 3.4 Conclusions 23 3.4 Conclusions
Page 35 and 36: 3.4 Conclusions 25 G−CMA−ES (5
Page 37: 3.4 Conclusions 27 Table 3.4: The m
Page 40 and 41: 30 Ant Colony Optimization for Mixe
Page 66 and 67: 56 Conclusions and Future Work of t
Page 69 and 70: Chapter 6 Appendix 6.1 Mathematical
Page 71 and 72: 6.1 Mathematical formulation of eng
Page 73 and 74: 6.1 Mathematical formulation of eng
Page 75: Bibliography [1] K. Abhishek, S. Le
Page 79 and 80: BIBLIOGRAPHY 69 [44] Q. He and L. W
Page 81 and 82: BIBLIOGRAPHY 71 [65] S. Lucidi, V.
Page 83 and 84: BIBLIOGRAPHY 73 [87] Thomas Stützl
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