Discrete optimal sizing of truss using adaptive directional differential evolution

- Journal title : Advances in Computational Design
- Volume 1, Issue 3, 2016, pp.275-296
- Publisher : Techno-Press
- DOI : 10.12989/acd.2016.1.3.275

Title & Authors

Discrete optimal sizing of truss using adaptive directional differential evolution

Pham, Anh H.;

Pham, Anh H.;

Abstract

This article presents an adaptive directional differential evolution (ADDE) algorithm and its application in solving discrete sizing truss optimization problems. The algorithm is featured by a new self-adaptation approach and a simple directional strategy. In the adaptation approach, the mutation operator is adjusted in accordance with the change of population diversity, which can well balance between global exploration and local exploitation as well as locate the promising solutions. The directional strategy is based on the order relation between two difference solutions chosen for mutation and can bias the search direction for increasing the possibility of finding improved solutions. In addition, a new scaling factor is introduced as a vector of uniform random variables to maintain the diversity without crossover operation. Numerical results show that the optimal solutions of ADDE are as good as or better than those from some modern metaheuristics in the literature, while ADDE often uses fewer structural analyses.

Keywords

adaptive directional differential evolution;population diversity;truss sizing optimization;discrete variables;

Language

English

Cited by

References

1.

Azad, S.K. and Hasancebi, O. (2014), "An elitist self-adaptive step-size search for structural design optimization", Appl. Soft Comput., 19, 226-235.

2.

Azad, S.K. and Hasancebi, O. (2015), "Discrete sizing optimization of steel trusses under multiple displacement constraints and load cases using guided stochastic search technique", Struct. Multidisciplin. Optimiz., 52(2), 383-404.

3.

Azad, S.K., Hasancebi, O. and Saka, M.P. (2014), "Guided stochastic search technique for discrete sizing optimization of steel trusses: A design-driven heuristic approach", Comput. Struct., 134, 62-74.

4.

Azad, S.K., Hasancebi, O., Azad, S.K. and Erol, O.K. (2013), "Upper bound strategy in optimum design of truss structures: A big bang-big crunch algorithm based application", Adv. Struct. Eng., 16(6), 1035-1046.

5.

Bennage, W.A. and Dhingra, A.K. (1995a), "Optimization of truss topology using tabu search", Int. J. Numer. Meth. Eng., 38(23), 4035-4052.

6.

Bennage, W.A. and Dhingra, A.K. (1995b), "Single and multiobjective structural optimization in discretecontinuous variables using simulated annealing", Int. J. Numer. Meth. Eng., 38(16), 2753-2773.

7.

Bland, J.A. (2001), "Optimal structural design by ant colony optimization", Eng. Optimiz., 33(4), 425-443.

8.

Bureerat, S. and Pholdee, N. (2015), "Optimal truss sizing using an adaptive differential evolution algorithm", J. Comput. Civ. Eng., 30(2), 04015019.

9.

Camp, C.V. (2007), "Design of space trusses using Big Bang-Big Crunch optimization", J. Struct. Eng., 133(7), 999-1008.

10.

Camp, C.V. and Bichon, B.J. (2004), "Design of space trusses using ant colony optimization", J. Struct. Eng., 130(5), 741-751.

11.

Camp, C.V. and Farshchin, M. (2014), "Design of space trusses using modified teaching-learning based optimization", Eng. Struct., 62, 87-97.

12.

Das, S., Abraham, A., Chakraborty, U.K. and Konar, A. (2009), "Differential evolution using a neighborhood-based mutation operator", Evolutionary Computation, IEEE Transactions on, 13(3), 526-553.

13.

Das, S. and Suganthan, P.N. (2011), "Differential evolution: a survey of the state-of-the-art", Evolutionary Computation, IEEE Transactions on, 15(1), 4-31.

14.

Deb, K. (2000), "An efficient constraint handling method for genetic algorithms", Comput. Meth. Appl. Mech. Eng., 186(2), 311-338.

15.

Elsayed, S.M., Sarker, R.A. and Essam, D.L. (2011), "Differential evolution with multiple strategies for solving CEC2011 real-world numerical optimization problems", Evolutionary Computation (CEC), 2011 IEEE Congress on, IEEE.

16.

Gong, W., Cai, Z., Ling, C.X. and Li, H. (2011), "Enhanced differential evolution with adaptive strategies for numerical optimization", Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 41(2), 397-413.

17.

Hajela, P. and Lin, C.Y. (1992), "Genetic search strategies in multicriterion optimal design", Struct. Optimiz., 4(2), 99-107.

18.

Hasancebi, O. and Azad, S.K. (2014), "Discrete size optimization of steel trusses using a refined big bangbig crunch algorithm", Eng. Optimiz., 46(1), 61-83.

19.

Hasancebi, O. and Azad, S.K. (2015), "Adaptive dimensional search: a new metaheuristic algorithm for discrete truss sizing optimization", Comput. Struct., 154, 1-16.

20.

Ho-Huu, V., Nguyen-Thoi, T., Vo-Duy, T. and Nguyen-Trang, T. (2016), "An adaptive elitist differential evolution for optimization of truss structures with discrete design variables", Comput. Struct., 165, 59-75.

21.

Kaveh, A. and Ahmadi, B. (2014), "Sizing, geometry and topology optimization of trusses using force method and supervised charged system search", Struct. Eng. Mech., 50(3), 365-382.

22.

Kaveh, A. and Ghazaan, M.I. (2014), "Enhanced colliding bodies optimization for design problems with continuous and discrete variables", Adv. Eng. Soft., 77, 66-75.

23.

Kaveh, A. and Ghazaan, M.I. (2015), "A comparative study of CBO and ECBO for optimal design of skeletal structures", Comput. Struct., 153, 137-147.

24.

Kaveh, A. and Mahdavi, V.R. (2014), "Colliding bodies optimization method for optimum discrete design of truss structures", Comput. Struct., 139, 43-53.

25.

Kaveh, A. and Zolghadr, A. (2012), "Truss optimization with natural frequency constraints using a hybridized CSS-BBBC algorithm with trap recognition capability", Comput. Struct., 102, 14-27.

26.

Krempser, E., Bernardino, H., Barbosa, H. and Lemonge, A. (2012), "Differential evolution assisted by surrogate models for structural optimization problems", Proceedings of the international conference on computational structures technology (CST). Civil-Comp Press.

27.

Kushida, J.I., Hara, A. and Takahama, T. (2015), "Rank-based differential evolution with multiple mutation strategies for large scale global optimization", Evolutionary Computation (CEC), 2015 IEEE Congress on, IEEE.

28.

Lampinen, J. and Zelinka, I. (1999), "Mixed integer-discrete-continuous optimization by differential evolution", Proceedings of the 5th International Conference on Soft Computing.

29.

Lee, K.S., Geem, Z.W., Lee, S.H. and Bae, K.W. (2005), "The harmony search heuristic algorithm for discrete structural optimization", Eng. Optimiz., 37(7), 663-684.

30.

Li, L.J., Huang, Z.B. and Liu, F. (2009), "A heuristic particle swarm optimization method for truss structures with discrete variables", Comput. Struct., 87(7), 435-443.

31.

Mallipeddi, R., Suganthan, P.N., Pan, Q.K. and Tasgetiren, M.F. (2011), "Differential evolution algorithm with ensemble of parameters and mutation strategies", Appl. Soft Comput., 11(2), 1679-1696.

32.

Pholdee, N., Bureerat, S., Park, W.W., Kim, D.K., Im, Y.T., Kwon, H.C. and Chun, M.S. (2015), "Optimization of flatness of strip during coiling process based on evolutionary algorithms", Int. J. Precision Eng. Manufact., 16(7), 1493-1499.

33.

Qin, A.K. and Suganthan, P.N. (2005), "Self-adaptive differential evolution algorithm for numerical optimization", 2005 IEEE congress on evolutionary computation, IEEE.

34.

Rahnamayan, S., Tizhoosh, H.R. and Salama, M. (2008), "Opposition-based differential evolution", Evolutionary Computation, IEEE Transactions on, 12(1), 64-79.

35.

Rajeev, S. and Krishnamoorthy, C.S. (1992), "Discrete optimization of structures using genetic algorithms", J. Struct. Eng., 118(5), 1233-1250.

36.

Sadollah, A., Bahreininejad, A., Eskandar, H. and Hamdi, M. (2012), "Mine blast algorithm for optimization of truss structures with discrete variables", Comput. Struct., 102, 49-63.

37.

Sadollah, A., Eskandar, H., Bahreininejad, A. and Kim, J.H. (2015), "Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures", Comput. Struct., 149, 1-16.

38.

Stolpe, M. (2015), "Truss optimization with discrete design variables: a critical review", Struct. Multidisciplin. Optimiz., 53(2), 349-374.

39.

Storn, R. and Price, K. (1997), "Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces", J. Glob. Optimiz., 11(4), 341-359.

40.

Takahama, T. and Sakai, S. (2012), "Differential evolution with dynamic strategy and parameter selection by detecting landscape modality", Evolutionary Computation (CEC), 2012 IEEE Congress on, IEEE.

41.

Tanabe, R. and Fukunaga, A. (2013), "Success-history based parameter adaptation for differential evolution", 2013 IEEE Congress on Evolutionary Computation, IEEE.

42.

Wang, Y., Cai, Z. and Zhang, Q. (2011), "Differential evolution with composite trial vector generation strategies and control parameters", Evolutionary Computation, IEEE Transactions on, 15(1), 55-66.

43.

Wang, Z., Tang, H. and Li, P. (2009), "Optimum design of truss structures based on differential evolution strategy", Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on, IEEE.

44.

Wu, G., Mallipeddi, R., Suganthan, P.N., Wang, R. and Chen, H. (2016), "Differential evolution with multipopulation based ensemble of mutation strategies", Inform. Sci., 329, 329-345.

45.

Xiang, W.L., Meng, X.L., An, M.Q., Li, Y.Z. and Gao, M.X. (2015), "An Enhanced Differential Evolution Algorithm Based on Multiple Mutation Strategies", Computational intelligence and neuroscience, 2015.

46.

Yang, Y. and Yao, M. (2014), "Differential evolution with M-fitness method", Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on, IEEE.

47.

Zamuda, A., Brest, J. and Mezura-Montes, E. (2013), "Structured population size reduction differential evolution with multiple mutation strategies on CEC 2013 real parameter optimization", Evolutionary Computation (CEC), 2013 IEEE Congress on, IEEE.