The computing of the optimal power consumption for semi-track air-cushion vehicle using hybrid generalized extremal optimization. (English) Zbl 1205.93112
Summary: A new stochastic method named hybrid generalized extremal optimization (HGEO) is proposed in this paper. It combines genetic algorithms (GAs) and generalized extremal optimization (GEO). In order to extend GEO’s mutation operator to accelerate convergence speed and be easily incorporated into HGEO, the real coded GEO is first developed to population-base GEO (PGEO), and then incorporated into the HGEO in the paper. Constraints consideration for using the HGEO and the effects of related operators are also investigated. Finally, the performance of the HGEO is fully investigated compared with other related algorithms to find the optimal power consumption for the semi-track air-cushion vehicle (STACV). The results show that the HGEO has better performance than GAs or other related simpler algorithms.
MSC:
| 93C95 | Application models in control theory |
| 90C90 | Applications of mathematical programming |
| 68T05 | Learning and adaptive systems in artificial intelligence |
References:
| [1] | X. Wang, Z. Luo, B.C. Chen, Y.W. Shi, S.J. Ning, Study on automatic control system of a semi-tracked air-cushion vehicle, in: Proceedings of the IEEE International Conference on Vehicle Electronics, 1999.; X. Wang, Z. Luo, B.C. Chen, Y.W. Shi, S.J. Ning, Study on automatic control system of a semi-tracked air-cushion vehicle, in: Proceedings of the IEEE International Conference on Vehicle Electronics, 1999. |
| [2] | Luo, Zhe; Yu, Fan; Chen, Bingcong, Design of a novel semi-tracked air-cushion vehicle for soft terrain, Int. J. Vehicle Design, 31, 1, 112-123 (2003) |
| [3] | Luo, Zhe; Yu, Fan, Load distribution control system design for a semi-track air-cushion vehicle, J. Terramech., 44, 4, 319-325 (2007) |
| [4] | Kirkpatrick, S.; Gelatt, C. D.; Vecchi, M. P., Optimization by simulated annealing, Science, 220, 4598, 671-678 (1983) · Zbl 1225.90162 |
| [5] | Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning (1989), Addison-Wesley Publishing Company: Addison-Wesley Publishing Company Reading, MA · Zbl 0721.68056 |
| [6] | Runarsson, T. P.; Yao, X., Stochastic ranking for constrained evolutionary optimization, IEEE Trans. Evolut. Comput., 4, 284-294 (2000) |
| [7] | Mezura-Montes, E.; Coello, C. A.C., A simple multimembered evolution strategy to solve constrained optimization problems, IEEE Trans. Evolut. Comput., 9, 1, 1-17 (2005) |
| [8] | Boettcher, S.; Percus, A. G., Nature’s way of optimizing, Artif. Intell., 119, 275-286 (2000) · Zbl 0949.90075 |
| [9] | Boettcher, S., Extremal optimization: heuristics via coevolutionary avalanches, Comput. Sci. Eng., 2, 6, 75-82 (2000) |
| [10] | Bak, P.; Tang, C.; Wiesenfeld, K., Self-organized criticality: an explanation of \(1/f\) noise, Phys. Rev. Lett., 59, 381-384 (1987) |
| [11] | Bak, P.; Tang, C.; Wiesenfeld, K., Self-organized criticality, Phys. Rev. Lett. A, 38, 1, 364-374 (1988) · Zbl 1230.37103 |
| [12] | Bak, P.; Sneppen, K., Punctuated equilibrium and criticality in a simple model of evolution, Phys. Rev. Lett., 71, 24, 4083-4086 (1993) |
| [13] | Menai, M. E.; Batouche, M., Efficient initial solution to extremal optimization algorithm for weighted MAXSAT problem, IEA/AIE 2003, 592-603 (2003) · Zbl 1039.68861 |
| [14] | Boettcher, S.; Percus, A. G., Extremal optimization at the phase transition of the three-coloring problem, Phys. Rev., E69, 066703 (2004) |
| [15] | Boettcher, S., Extremal optimization for the Sherrington-Kirkpatrick spin glass, Eur. Phys. J., B46, 501-505 (2005) |
| [16] | I. Moser, T. Hendtlass, Solving problems with hidden dynamics-comparison of extremal optimization and ant colony system, in: Proceedings of the 2006 IEEE Congress on Evolutionary Computation (CEC’2006), 2006, pp. 1248-1255.; I. Moser, T. Hendtlass, Solving problems with hidden dynamics-comparison of extremal optimization and ant colony system, in: Proceedings of the 2006 IEEE Congress on Evolutionary Computation (CEC’2006), 2006, pp. 1248-1255. |
| [17] | Boettcher, S.; Percus, A. G., Optimization with extremal dynamics, Phys. Rev. Lett., 86, 5211-5214 (2001) |
| [18] | De Sousa, F. L.; Vlassov, V.; Ramos, F. M., Generalized extremal optimization: an application in heat pipe design, Appl. Math. Model., 28, 911-931 (2004) · Zbl 1147.90425 |
| [19] | Zhou, Tao; Bai, Wen-Jie; Cheng, Long-Jiu; Wang, Bing-Hong, Continuous extremal optimization for Lennard-Jones Clusters, Phys. Rev. E, 72, 016702 (2005) |
| [20] | Min-Rong Chen, Yong-Zai Lu, Genke Yang, Population-based extremal optimization with adaptive lévy mutation for constrained optimization, in: Proceedings of the 2006 International Conference on Computational Intelligence and Security (CIS’06), 2006.; Min-Rong Chen, Yong-Zai Lu, Genke Yang, Population-based extremal optimization with adaptive lévy mutation for constrained optimization, in: Proceedings of the 2006 International Conference on Computational Intelligence and Security (CIS’06), 2006. |
| [21] | M. Randall, A. Lewis, An extended extremal optimization model for parallel architectures, in: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing, 2006.; M. Randall, A. Lewis, An extended extremal optimization model for parallel architectures, in: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing, 2006. |
| [22] | Melkemi, K. E.; Batouche, M.; Foufou, S., A multiagent system approach for image segmentation using genetic algorithms and extremal optimization heuristics, Pattern Recognit. Lett., 27, 1230-1238 (2006) |
| [23] | Hamacher, K., Adaptive extremal optimization by detrended fluctuation analysis, J. Comput. Phys., 227, 1500-1509 (2007) · Zbl 1128.65041 |
| [24] | Chen, Min-Rong; Lu, Yong-Zai, A novel elitist multiobjective optimization algorithm: multiobjective extremal optimization, Eur. J. Oper. Res., 188, 637-651 (2008) · Zbl 1144.90475 |
| [25] | Wong, J. Y., Theory of Ground Vehicle (2001), John Wiley & Sons, Inc. |
| [26] | Y.G. Zhang, Research on structure design and energy saving for semi-track air-cushion vehicle, Doctoral Dissertation, Jilin University, Changchun, China, 2000.; Y.G. Zhang, Research on structure design and energy saving for semi-track air-cushion vehicle, Doctoral Dissertation, Jilin University, Changchun, China, 2000. |
| [27] | Siriwardene, N. R.; Perera, B. J.C., Selection of genetic algorithm operators for urban drainage model parameter optimization, Math. Comput. Modell., 44, 415-429 (2006) · Zbl 1170.90527 |
| [28] | Goldberg, D. E.; Deb, K., A comparative analysis of selection schemes used in genetic algorithms, (Rawlins, G. J., Foundations of Genetic Algorithms (1991), Morgan Kaufman Publishers: Morgan Kaufman Publishers San Mateo, California), 69-93 |
| [29] | Kellegöz, Talip; Toklu, Bilal; Wilson, John, Comparing efficiencies of genetic crossover operators for one machine total weighted tardiness problem, Appl. Math. Comput., 199, 590-598 (2008) · Zbl 1140.90402 |
| [30] | Chang, Wei-Der, A multi-crossover genetic approach to multivariable PID controllers tuning, Exp. Syst. Appl., 33, 620-626 (2007) |
| [31] | Deep, Kusum; Thakur, Manoj, A new crossover operator for real coded genetic algorithms, Appl. Math. Comput., 188, 895-911 (2007) · Zbl 1137.90726 |
| [32] | Brooks, R. R.; Iyengar, S. S.; Chen, J., Automatic correlation and calibration of noisy sensor readings using elite genetic algorithms, Artif. Intell., 84, 339-354 (1996) |
| [33] | Djurišić, Aleksandra B., Elite genetic algorithms with adaptive mutations for solving continuous optimization problems-application to modeling of the optical constants of solids, Opt. Commun., 151, 147-159 (1998) |
| [34] | Zitzler, E.; Deb, K.; Thiele, L., Comparison of multiobjective evolutionary algorithms: empirical results, Evolut. Comput., 8, 2, 173-195 (2000) |
| [35] | J.A. Joines, C.R. Houck, On the use of non-stationary penalty functions to solve non-linear constrained optimization problems with GA’s, in: International Conference on Evolutionary Computation, 1994, pp. 579-584.; J.A. Joines, C.R. Houck, On the use of non-stationary penalty functions to solve non-linear constrained optimization problems with GA’s, in: International Conference on Evolutionary Computation, 1994, pp. 579-584. |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
