Hostname: page-component-848d4c4894-sjtt6 Total loading time: 0 Render date: 2024-06-20T22:27:10.112Z Has data issue: false hasContentIssue false

Human-computer co-operative co-evolutionary method and its application to a satellite module layout design problem

Published online by Cambridge University Press:  03 February 2016

J-Z. Huo
Affiliation:
School of Mechanical Engineering, Dalian University of Technology, Dalian, China
H-F. Teng
Affiliation:
School of Mechanical Engineering, Dalian University of Technology, Dalian, China
W. Sun
Affiliation:
School of Mechanical Engineering, Dalian University of Technology, Dalian, China
J. Chen
Affiliation:
Department of Naval Architecture and Ocean Engineering, Dalian University of Technology, Dalian, China

Abstract

The layout design of a satellite module is a complex mechanical layout problem. Its main difficulties lie in combinatorial explosion of computational complexity, engineering complexity, and applicability in engineering practice. Inspired by the human-computer cooperation ideas, a human–computer co-operative co-evolutionary method for optimising layout design of a satellite module is developed. This method constructs the diversity reference set by using the diversity intelligence solutions (DIs) that are created by using the combinatorial operators of differential evolution (DE) and the blend crossover operator (BLX-a). During the co-evolution process of the presented method, the AIs, the DIs and the algorithm solutions are expressed by unified encoding strings and incorporated together to create new co-operative solutions. An instance of a satellite module layout design is presented to demonstrate the feasibility and effectiveness of the proposed method. Compared with the co-evolutionary approach and the all-at-once optimisation approaches, computational results show that the proposed method not only can produce better solutions, but also can better balance the conflicting objectives on the trade-off issues.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2010 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Sun, Z.G., Teng, H.F. and Liu, Z. W., Several key problems in automatic layout design of spacecraft modules, Chinese J Prog in Natural Science, 2003, 13, (11), pp 801808.Google Scholar
2. Braun, R.D., Moore, A.A. and Kroo, I.M., Collaborative approach to launch vehicle design, J Spacecraft and Rockets, 1997, 34, (4), pp 478486.10.2514/2.3237Google Scholar
3. Kamran, D., Maziar, A. and Hossein, S.F., ‘FARAGAM’ algorithm in satellite layout, 2001, Proceedings of Sixth Asia-Pacific Conference on Multilateral Co-operation in Space Technology and Application. Beijing, China, pp 120127.Google Scholar
4. Grignon, P.M. and Fadel, G.M., A GA-based configuration design optimization method, J Mechanical Design, 2004, 126, pp 615.Google Scholar
5. Ferebee, M.J. and Allen, C.L., Optimization of payload placement on an arbitrary spacecraft, J Spacecraft and Rockets, 1991, 28, (5), pp 612614.Google Scholar
6. Tanner, S. and Fennel, R., The placement of equipment in the space 16. station freedom using constraint based reasoning, 1991, Proceedings AAAI Conference on Innovative Applications of AI, Anaheim, USA, pp 5171.Google Scholar
7. Cagan, J., Degentesh, D. and Yin, S., A simulated annealing-based algorithm using hierarchical models for general three-dimensional component layout, Computer-Aided Design, 1998, 30, (10), pp 781790.Google Scholar
8. Qian, Z.Q., Teng, H.F. and Sun, Z.G., Human-computer interactive genetic algorithm and its application to constrained layout optimization, Chinese Journal of Computers (in Chinese), 2001, 24, (5), pp f299302.Google Scholar
9. Liu, Z.W. and Teng, H.F., Human-computer co-operative layout design method and its application, Computers and Industrial Engineering, 2008, 55, pp 735757.Google Scholar
10. Sun, W.J. and Scchen, C., Efficient and effective placement for very large circuits, 1995, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 14, (3), pp 349359.Google Scholar
11. Lenat, D.B. and Feigenbaum, E.A., On the thresholds of knowledge, 1988, Proceedings of International Workshop on Artificial Intelligence for Industrial Applications, Oakland, pp 291300.Google Scholar
12. Potter, M.A and De Jong, K.A., A co-operative coevolutionary approach to function optimization, 1994, Proceedings of the Third Conference on Parallel Problem Solving from Nature. Jerusalem, Israel, pp 249257.Google Scholar
13. Sung-Bae, C., Towards creative evolutionary systems with interactive algorithm, Applied Intelligence, 2002, 16, (11), pp 129138.Google Scholar
14. Kosorukoff, A., Human based genetic algorithm, 2001, IEEE International Conference on Systems, Man and Cybernetics, Tucson, pp 34643469.Google Scholar
15. Murthy, S., Akkiraju, R. and Rachlin, J., et al. Agent-based co operative scheduling, 1997, Proceedings of AAAI Workshop on Constraints and Agents, USA, pp 112117.Google Scholar
16. Liu, J. and Teng, H. F., Human-genetic algorithm co-operation and its interface, 2002, Proceedings of Fifth Asia Pacific Conference on Computer Human Interaction (APCHI), Beijing, China, pp. 378387.Google Scholar
17. Babu, B.V. and Munawar, S.A., Differential Evolution for the Optimal Design of Heat Exchangers, 2000, Proceedings of All India Seminar on Chemical Engineering Progress on Resource Development: A Vision 2010 and Beyond.Google Scholar
18. Lozano, M., Herrera, F. and Verdegay, J.L., Tackling real-coded genetic algorithms: Operators and tools for the behavioral analysis, Artificial Intelligence Reviews, 1998, 12, (4), pp 265319.Google Scholar
19. Nomura, T., Shimohara, K., An analysis of two-parent recombinations for real-valued chromosomes in an infinite population, Evolutionary Computation J, 2001, 9, (3), pp 283308.Google Scholar
20. Huo, J. Z. and Teng, H. F., Optimal layout design of a satellite module using a coevolutionary method with heuristic rules, J Aerospace Eng, 2009, 22, (2), pp 101111.Google Scholar
21. Shi, Y.J., The Co-operative Co-Evolutionary Differential Evolution and Its Applications for Complex Layout Optimization, 2005, PhD dissertation (in Chinese), Dalian University of Technology, China.Google Scholar
22. Sun, Z.G., Sequential and Physical Decomposition Methods for a Layout Design Problem of Spacecrafts, 2005, PhD dissertation (in Chinese), Dalian University of Technology, China.Google Scholar
23. Shi, Y.J., Teng, H.F. and Li, Z.Q., Co-operative co-evolutionary differential evolution for function optimization, Lecture Notes in Computer Science, 2005, 3611, pp 10801088.Google Scholar
24. Sun, Z.G., Teng, H.F. and Liu, D.Q., Optimal layout design of a satellite module, Engineering Optimization, 2003, 35, (6), pp 513529 Google Scholar