PSO-DE混合式搜尋法應用於結構最佳化設計的研究

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鍾昀展(Yun-zhan Zhong) 查詢紙本館藏

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土木工程學系

論文名稱

PSO-DE混合式搜尋法應用於結構最佳化設計的研究
(PSO-DE hybrid search algorithm is applied to optimum structural design)

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摘要(中)

本文主要是針對離散變數、連續變數、混合變數之結構最佳化設計問題，提出以粒子群演算法(Particle Swarm Optimization , PSO)為基礎結合差分演化法(Differential Evolution , DE)的一種混合啟發式搜尋法，稱為PSO-DE。PSO和DE均為一隨機搜尋法，且都具有全域搜尋的能力。從以往的研究結果中可看出PSO的缺點，即在求解最佳化問題的搜尋初期收斂速度較快，到了後期搜尋階段隨著粒子群逐漸往群體最佳解的粒子靠近，因而喪失了整個群體的多樣性，導致搜尋後期收斂速度變慢且粒子易陷入局部最佳解。為了解決此一缺點，本文將採用DE演算法來增加PSO群體中之多樣性，期望能降低粒子容易陷入局部最佳解的機率。然後藉由多種不同設計變數類型的結構輕量化設計問題來探討其適用性和影響求解品質與效率的相關參數，並由設計結果之比較，來探討本文所發展之PSO-DE的優缺點。比較結果發現PSO-DE在求解多數混合變數和離散變數之結構最佳化問題時，都具有不錯的求解穩定性和搜尋性能。

摘要(英)

This article is devoted to the presentation of a hybrid heuristic searching algorithm, namely PSO-DE, for the optimum design of structures with discrete, continuous and mixed variables. PSO (Particle Swarm Optimization) and DE (Differential Evolution) are both the random search methods and capable of performing global search. The main deficiency of the PSO is that all particles have the tendency to fly to the current best solution which may be a local optimum or a solution near local optimum. In this case, all particles will move toward to a small region and the global exploration ability will be weakened. To overcome the drawback, this research uses the DE algorithm to increase the diversity of PSO groups, hoping to reduce the probability of particles that trapped in local minimum. More than ten typical structures in the literature are used to validate the effectiveness of the algorithms. The results from comparative studies of the PSO-DE against other optimization algorithms are reported to show the solution quality of the proposed PSO-DE algorithm.

關鍵字(中)

★ 結構輕量化設計
★ 混合啟發式搜尋法
★ 粒子群演算法
★ 差分演化法

關鍵字(英)

★ PSO
★ DE
★ optimum structural design
★ hybrid heuristic search algorithm

論文目次

目錄
目錄I
表目錄IV
圖目錄VI
第一章緒論1
1.1研究動機與目的1
1.2文獻回顧4
1.2.1模擬退火法(Simulated Annealing, SA)5
1.2.2遺傳演算法(Genetic algorithms, GA)6
1.2.3粒子群演算法(Particle Swarm Optimization, PSO)7
1.2.4和聲搜尋法(Harmony Search, HS)9
1.2.5差分演化法(Defferential Evolution,DE)10
1.3研究方法與內容11
第二章PSO演算法和DE演算法12
2.1最佳化問題之數學模式12
2.2粒子群演算法(PSO)13
2.2.1引言13
2.2.2PSO基本模式15
2.2.3常數慣性權重16
2.2.4線性慣量遞減17
2.2.5最大速度限制18
2.2.6壓縮因子18
2.2.7動態慣量及最大速度遞減19
2.2.8PSO之演算流程20
2.3差分演化法(DE)23
2.3.1引言23
2.3.2DE基本模式23
2.3.3DE的挑選策略24
2.3.4DE之演算流程25
第三章PSO-DE混合式演算法28
3.1引言28
3.2束制函數的處理與適應函數28
3.3PSO-DE演算法30
3.4測試算例32
3.4.122桿平面桁架33
3.5突變因子F的型態38
3.5.1測試比較39
3.5.2小結 43
第四章數值算例與參數研究44
4.1測試算例簡介44
4.2PSO-DE之參數研究45
4.2.110桿平面桁架45
4.2.1.1PSO-DE參數研究47
4.2.1.2結果比較61
4.2.1.3小結62
4.2.218桿平面桁架63
4.2.2.1PSO-DE參數研究65
4.2.2.2結果比較79
4.2.2.3小結85
4.3不同類型設計例之設計結果86
4.3.1類型(一)：52桿空間桁架(I)86
4.3.2類型(二)：25桿空間桁架(I)100
4.3.3類型(二)：160桿空間桁架108
4.3.4類型(二)：雙跨五層平面構架113
4.3.5類型(二)：單跨八層平面構架118
4.3.6類型(三)：25桿空間桁架(II)122
4.3.7類型(三)：25桿空間桁架(III)131
4.3.8類型(三)：39桿空間桁架 138
4.3.9類型(三)：52桿空間桁架(II)148
第五章結論與建議161
5.1結論與建議161
5.2未來研究方向163
參考文獻164
附錄A 22桿平面桁架細部資料及設計結果173
A.1 細部設計資料173
A.2 MPSO-SA-C3E設計結果174
附錄B 10桿平面桁架細部資料及設計結果175
B.1 細部設計資料175
B.2 MPSO-SA-C3E設計結果176
附錄C 18桿平面桁架細部資料及設計結果177
C.1 細部設計資料177
C.2 MPSO-SA-C3E設計結果178
附錄D 52桿空間桁架(I)細部資料及設計結果179
D.1 細部設計資料179
D.2 MPSO-SA-C3E設計結果180
附錄E 25桿空間桁架(I)細部資料及設計結果182
E.1 細部設計資料182
E.2 MPSO-SA-C3E設計結果183
附錄F 160桿空間桁架細部資料及設計結果185
F.1 細部設計資料185
F.2 MPSO-SA-C3E設計結果189
附錄G 雙跨五層平面構架細部資料及設計結果196
G.1 細部設計資料196
G.2 MPSO-SA-C3E設計結果198
附錄H 單跨八層平面構架細部資料及設計結果199
H.1 細部設計資料199
H.2 MPSO-SA-C3E設計結果205
附錄I 25桿空間桁架(II)細部資料及設計結果206
I.1 細部設計資料206
I.2 MPSO-SA-C3E設計結果207
附錄J 25桿空間桁架(III)細部資料及設計結果208
J.1 細部設計資料208
J.2 MPSO-SA-C3E設計結果209
附錄K 39桿空間桁架細部資料及設計結果210
K.1 細部設計資料210
K.2 MPSO-SA-C3E設計結果211
附錄L 52桿空間桁架(II)細部資料及設計結果212
L.1 細部設計資料212
L.2 MPSO-SA-C3E設計結果213

參考文獻

Aarts, E. H. L., and Korst, J. H. M., (1989) Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and Neural Computing, John Wiley & Sons, New York.
AISC, (1989) Manual of Construction : Allowable Stress Design, 9th Edition, Chicago, Illinois.
Angeline, P. J., (1998) “Using Selection to Improve Particle Swarm Optimization,” IEEE International conference on Evolutionary Computation, Anchorage, Alaska, May 4- 9, pp. 84?89.
AL-Kazemi, B., and Mohan, C. K., (2002) “Multi-Phase Generalization of the Particle Swarm Optimization Algorithm,” Proceedings of the IEEE Congress on Evolutionary Computation, Honolulu, HI, USA , May 12- May 17, Vol. 1, pp. 489?494.
Bremicker, M., Papalambros, P. Y., and Loh, H. T., (1990) “Solution of Mixed-Discrete Structural Optimization Problems with a New Sequential Linearization Algorithm,” Computers and Structures, Vol. 37( 4), pp. 451?461.
Chai, S., and Sun, H. C., (1996) “A Relative Difference Quotient Algorithm for Discrete Optimization,” Structural Optimization, Vol. 12(1), pp. 46?56.
Camp, C., Pezeshk, S., and Cao G., (1998) “Optimized Design of Two-Dimensional Structures Using a Genetic Algorithm,” Journal of Structural Engineering, ASCE, Vol. 124( 5), pp. 551?559.
Clerc, M., (1999) “The Swarm and the Queen: Towards a Deterministic and Adaptive Particle Swarm Optimization,” Proceedings of the Congress on Evolutionary Computation, Washington, DC, Vol. 3, pp. 1951?1957.
Carlisle, A., and Dozier, G., (2001) “An off-the-shelf PSO,” Proceedings of the Workshop on Particle Swarm Optimization, Indianapolis, IN, USA, Vol. 1, pp. 1?6.
Coello, C. A., (2002) “Theoretial and Numerical Constraint-Handing Techniques Used with Evolutionary Algorithms: A Survey of the State of the Art,” Computer Methods in Applied Mechanics and Engineering, Vol. 191(12), pp. 1245?1287.
De Jong, K. A., (1975) “An Analysis of the Behavior of a Class of Genetic Adaptive Systems,” Ph.D. Dissertation, University of Michigan, Dissertation Abstracts International, Vol. 36(10), 5140B. (University Microfilms No. 76?9381).
Davis, J. S., (1991) Handbook of Genetic Algorithms, Van Nostrand Reinhold.
Deb, K., Gulati, S., and Chakrabarti, S., (1998) “Optimal Truss-Structure Design Using Real-Coded Genetic Algorithms,” Proceedings of the Third Annual Conference, University of Wisconsin pp. 479?486.
Eberhart, R. C., and Kennedy, J., (1995a) “A New Optimizer Using Particle Swarm Theory,” Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39?43.
Eberhart, R. C., and Kennedy, J., (1995b) “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks, Washington, DC, Vol. IV, pp. 1942?1948.
Eberhart, R. C., and Shi, Y., (1998) “Comparison Between Genetic Algorithms and Particle Swarm Optimization,” In: Proceedings of the Seventh Annual Conference on Evolutionary Programming, San Diego, CA, pp. 611?616.
Eberhart, R. C., and Shi, Y., (2000) “Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization,” Proceedings of the Congress on Evolutionary Computation, San Diego, CA, Vol. 1, pp. 84?88.
Erbatur, F., Hasancebi, O., Tutuncu, I., and Kilic, H., (2000) “Optimal Design of Planar and Space Structures with Genetic Algorithms,” Computers and Structures, Vol. 75(2), pp. 209?224.
Fourie, P. C., and Groenwold A. A., (2002) “The Particle Swarm Optimization Algorithm in Size and Shape Optimization,” Structural and Multidisciplinary Optimization, Vol. 23(4), pp. 259?267.
Geem, Z. W., Kim, J. H., and Loganathan, G. V., (2001) “A New Heuristic Optimization Algorithm: Harmony Search,” Simulation, Vol. 76(2), pp.60-68.
Geem, Z. W., Kim, J. H., and Loganathan, G.V., (2002) “Harmony search optimization: Application to pipe network design,” Int. J. Modell. Simulation, Vol. 22(2), pp. 125-133.
Groenwold, A. A., and Stander, N., (1997) “Optimal Discrete Sizing of Truss Structures Subject to Buckling Constraints,” Structural Optimization, Vol. 14, pp. 71?80.
Groenwold, A. A., Stander, N., and Snyman, J. A., (1999) “A Regional Genetic Algorithms for the Discrete Optimal Design of Truss Structures,” International Journal for Numerical Methods in Engineering, Vol. 44(6), pp. 749?766.
Holland, J. H., (1962) “Outline for a Logical Theory of Adaptive System,” Journal of the Association for Computing Machinery, Vol. 3( 3), pp. 297?314.
Hu, X., and Eberhart, R. C., (2002) “Adaptive Particle Swarm Optimization: Detection and Response to Dynamic System,” Proceedings of the IEEE Congress on Evolutionary Computation, Indianapolis, IN, USA, pp. 1666?1670.
Hasançebi, O., and Erbatur, F., (2001) “Layout Optimization of Trusses Using Improved GA Methodlogies,” ACTA Mechanica, Vol. 146, pp. 87?107.
Imai, K., (1978) “Configuration Optimization of Trusses by the Multiplier Method,” Rpt. No. UCLA-ENG-7842 Mechanics and Structures Department, School of Engineering and Applied Science, University of California, Los Angles, CA.
Juang, D. S., (2004) “Integrated Configuration and Discrete Sizing Optimization of Truss Structures Using Discrete Lagrangian Method,” Proceedings of the 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, Aug. 30-Sept. 1, Paper No. AIAA-2004-4535.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P., (1983) “Optimization by Simulated Annealing,” Science, Vol. 220(4598), pp.671?680.
Kennedy, J., and Eberhart, R. C., (2001) Swarm Intelligence, Morgan Kaufmann.
Krink, T., Vesterstorm J. S., and Riget, J., (2002) “Particle Swarm Optimization with Spatial Particle Extension,” Proceedings of the IEEE Congress on Evolutionary Computation, Honolulu, HI, USA, pp. 1474?1497.
Kim, M., (2003) “Solving Traveling Salesman Problem Using Harmony Search,” ENCE 677, Fall.
Kaveh, A., and Kalatjari, V., (2004) “Size/Geometry Optimization of Trusses by the Force Method and Genetic Algorithm,” Zeitschrift fur Angewandte Mathematik and Mechanics, Vol. 84, (5), pp. 347?357.
Li, L. L., Wang, L., and Liu, L., (2006) “An effective hybrid PSOSA strategy for optimization and its application to parameter estimation.” Applied Mathematics and Computation Vol. 179(1) pp. 135-146.
Lipson, S. L., and Gwin, L. B., (1977) “The Complex Method Applied to Optimal Truss Configuration,” Computers and Structures, Vol. 7(3), pp. 461?468.
Metropolis, N., Rosenbluth, A. W., Teller, A. H., and Teller, E., (1953) “Equation of State Calculation by Fast Computing Machines,” Journal of Chemical Physics, Vol. 21(6), pp. 1087?1092.
Nanakorn, P., and Meesomklin, K., (2001) “An Adaptive Penalty Function in Genetic Algorithms for Structural Design Optimization,” Computers and Structures, Vol. 79(29), pp. 2527?2539.
Price Kenneth V., (1999) “An Introduction to Differential Evolution,” in：Corne, D., Dorigo, M., Glover, F. (Eds.), New Ideas in Optimization, McGraw-Hill, London, pp. 79-108.
Pedersen, P., (1973) “Optimal Joint Positions for Space Trusses,” Journal of the Structural Division, ASCE, Vol. 99(12), pp. 2459?2475.
Price K., and Storn R., (1995) “Differential Evolution－A Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces,” Technical report TR-95-012, International Computer Science Institute, Berkeley, CA.
Price K., and Storn R., (1997) “Differential Evolution－A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces,” Journal of Global Optimization, Vol.11(4), pp. 341-359.
Rajeev, S., and Krishnamoorthy, C. S., (1997) “Genetic Algorithms-based Methodologies for Design Optimization of Trusses,” Journal of Structural Engineering, ASCE, Vol. 123(3), pp. 350?358.
Ratnaweera, A., Halgamuge, SK., and Watson, HC., (2004) “Self-Organizing Hierarchical Particle Swarm Optimizer with Time-Varying Acceleration Coefficients,” IEEE Transactions on Evolutionary Computation, Vol. 8(3), pp. 240?255.
Shi, Y., and Eberhart, R. C., (1998a) “A Modified Particle Swarm Optimizer,” Proceedings of the IEEE International Conference on Evolutionary Computation, NJ, USA, pp. 69?73.
Shi, Y., and Eberhart, R. C., (1998b) “Parameter Selection in Particle Swarm Optimization,” V. W. Porto, N. Saravanan, D. Waagen, and A. E. Eiben (eds), Lecture Notes in Computer Science, 1447, Evolutionary Programming VII, Springer, Berlin, pp. 591?600.
Trosset, M. W., (2002) “What is Simulated Annealing,” Optimization and Engineering, Vol. 2, pp. 201－213.
Thierauf, G., and Cai, J., (1997) “Parallel Evolution Strategy for Solving Structural Optimization,” Engineering Structures, Vol. 19(4), pp. 318?324.
Whitley, D., (1989) “The Genitor Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best,” Proceeding of the Third International Conference on Genetic Algorithms, J.D. Schaffer, Morgan Kaufmann, San Mateo, California, pp. 116?121.
Wu, S. J., and Chow, P. T., (1995a) “The Application of Genetic Algorithms to Discrete Optimal Problems,” Journal of the Chinese Society of Mechanical Engineers, Vol. 16(6), pp. 587?598.
Wu, S. J., and Chow, P. T., (1995b) “Integrated Discrete and Configuration Optimization of Trusses Using Genetic Algorithms,” Computers and Structures, Vol. 55(4), pp. 695?702.
Wang, D., Zhang W. H., and Jiang, J. S., (2002) “Truss Shape Optimi -zation with Multiple Displacement Constraints,” Computer Methods in Applied Mechanics and Engineering, Vol. 191(33), pp. 3597?3612.
Xie, X. F., Zhang, W. J., and Yang, Z. L., (2002) “A Dissipative Particle Swarm Optimization,” Proceedings of the IEEE Congress on Evolutionary Computation, Honolulu, Hawaii, USA, Vol. 2, pp. 1456?1461.
Yang, J., and Soh, C. K., (1997) “Structural Optimization by Genetic Algorithms with Tournament Selection,” Journal of Computing in Civil Engineering, ASCE, Vol. 11( 3), pp. 195?200.
Ye, B., Zhu, C. Z., Guo, C. X., and Cao, Y. J., (2005) “Generating Extended Fuzzy Basis Function Networks Using Hybrid Algorithm,” Lecture Notes in Artificial Intelligence, Vol. 3613, pp. 79?88.
李世炳、鄒忠毅 (2002)，「簡介導引模擬退火法及其應用」，物理雙月刊，第二十四卷，第二期，第307?319頁。
林大為 (2009)，「結合模擬退火之改良粒子群演算法於結構最佳化設計的研究」，碩士論文，國立中央大學土木工程研究所，中壢市。
胡曉輝 (2002.4)，「粒子群優化算法介紹」，＜http://web.ics.purdue.edu/ ~hux/tutorials.shtml＞。
莊玟珊 (2007)，「PSO-SA混合搜尋法與其他結構最佳化設計之應用」，碩士論文，國立中央大學土木工程研究所，中壢市。
莊德興 (2004)，「桁架之形狀與離散斷面的整合輕量化設計」，第七屆結構工程研討會，桃園大溪。
張慰慈 (2003)，「DLM?GA混合搜尋法於結構離散最佳化設計之應用」，碩士論文，國立中央大學土木工程研究所，中壢市。
黃嘉進 (2007)，「桁架形狀與構件離散斷面之兩階段最佳化設計法」，碩士論文，國立中央大學土木工程研究所，中壢市。
赫然、王永吉、王青、周津慧、胡陳勇 (2005)，「一種改進的自適應逃逸微粒群算法及實驗分析」，軟件學報，第十六卷，第十二期，第2036?2044頁。
蔡清欉 (2003)，「以粒子群最佳化為基礎之電腦遊戲角色設計之研究」，碩士論文，東海大學資訊工程與科學研究所，台中市。
藍志浩 (2005)，「考慮動態反應束制及關連性離散變數之結構最佳化設計」，碩士論文，國立中央大學土木工程研究所，中壢市。
譚立靜、欒麗君、牛奔、孟亞寧 (2006)，「一種求解函數優化的新型混合優化算法」，遼寧工程技術大學機械工程學院，遼寧。
羅冠君 (2008)，「基於和聲搜尋法與離散拉格郎日法之混合演算法於結構最佳化設計的研究」，碩士論文，國立中央大學土木工程研究所，中壢市。

指導教授

莊德興(Der-Shin Juang)

審核日期

2011-1-25

推文