Structural designs (i.e. truss structures) are derived by the use of a threephase genetic optimization approach, where the minimization of volume is the objective of each truss structure considered. A genetic algorithm is employed which controls the three phase optimization technique. The first phase utilizes the conventional functionality of the genetic algorithm from an evolutionary perspective, however designer interaction by the use of constant rules is provided to ensure an effective evolutionary search outcome. The second phase enhances the best design constructed from phase one by the use of domain specific knowledge in the form of design rules. Phase three improves the final design assembled within phase two by the reduction of truss element areas. This refinement process ensures that the design constraints provided are active, indicating an optimal search solution. All phases operate from a global perspective; however the phase two optimization methodology operates from a more radical approach which encompasses the concept of designing from a “blank sheet of paper” point of view. Results are provided upon the conclusion of each truss example considered which includes the outcomes of each phase for comparison purposes.
References
[1]
Smith, J., Hodgins, J., Oppenheim, I. and Witkin, A. (2002) Creating Models of Truss Structures with Optimization. ACM Transactions on Graphics (TOG), 21, 295-301. https://doi.org/10.1145/566654.566580
[2]
Hamza, K., Mahmoud, H. and Saitou, K. (2003) Design Optimization of N-Shaped Roof Trusses Using Reactive Taboo Search. Applied Soft Computing, 3, 221-235.
https://doi.org/10.1016/S1568-4946(03)00036-X
[3]
Sandgren, E. and Cameron, T.M. (2002) Robust Design Optimization of Structures through Consideration of Variation. Computers and Structures, 80, 1605-1613.
https://doi.org/10.1016/S0045-7949(02)00160-8
[4]
Kepler, J. (2002) Structural Optimization as a Design and Styling Tool.
[5]
Leger, C. (2000) Performance Characterization of an Automated System for Robot Configuration Synthesis.
[6]
Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Boston.
[7]
Davis, L. (1991) Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York.
[8]
Logan, D.L. (2000) A First Course in the Finite Element Method Using AlgorTM. 2nd Edition, Brooks/Cole, Pacific Grove.
[9]
Microsoft Corporation (1998) Microsoft Visual Basic Version 6.0. Microsoft Corporation, Albuquerque.
[10]
Kawamura, H. and Ohmori, H. (2001) Computational Morphogenesis of Discrete Structures via Genetic Algorithms. Memoirs of the School of Engineering, Nagoya University, 53, 28-55.