以模擬最佳化求解具成本機率限制式之最大化系統可靠度冗餘配置問題

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研究生：	王昱翔 Wang, Yu-Hsiang
論文名稱：	以模擬最佳化求解具成本機率限制式之最大化系統可靠度冗餘配置問題 Solving Maximum System Reliability Redundancy Allocation Problem with Chance Constraint Using Simulation Optimization
指導教授：	張國浩 Chang, Kuo-Hao
口試委員:	劉建良 Liu, Chien-Liang 林春成 Lin, Chun-Cheng
學位類別：	碩士 Master
系所名稱：	工學院 - 工業工程與工程管理學系 Department of Industrial Engineering and Engineering Management
論文出版年：	2020
畢業學年度：	108
語文別：	中文
論文頁數：	48
中文關鍵詞：	冗餘配置問題、可靠度工程、模擬最佳化
外文關鍵詞：	Redundancy Allocation Problem, Reliability Engineering, Simulation Optimization
相關次數：	點閱：1 下載：0
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近年來，可靠度最佳化問題普遍受到重視，而冗餘配置問題(Redundancy Allocation Problem, RAP)便是其中一個熱門的研究領域。冗餘配置問題主要應用在大型且複雜的系統，像是電力系統、通訊系統或是製造系統，探討如何在滿足資源的限制之下，透過在每一個子系統(subsystem)中配置冗餘的備品，最大化整個系統的可靠度。在本論文中，主要分為兩個面向討論。第一，在現今的工業系統之下，單純的串並聯系統無法滿足實務上的應用，因此我們考慮一個一般化的拓樸結構系統。第二，此問題在資源的限制上採用了機率約束限制式，本研究並不嚴格限制資源的消耗，允許有少數情況超出資源限制，只要大多數的狀況下符合限制即可，而機率限制式本身為一相當複雜的問題，加上此問題隨機變數眾多，且網路可靠度僅可透過模擬方式取得，求解相當困難。本論文提出一個以模擬最佳化為基礎的演算法，使得我們能夠在考慮一般化拓樸結構的系統中求解，並在數值實驗中證明本論文之方法能夠更有效率的求解，且優於現存的求解方法。

The redundancy allocation problem (RAP) is an important reliability optimization problem and has been an active area for the past decades. In literature, most of these system reliability problems are considered in complex system such as electronic systems, power systems, telecommunication systems and manufacturing systems where the reliability of each components is considered as a precise value. In this paper, we extend RAP to a more generalized situation. First, the network topology is generalized, the components in the system can be series-parallel or any logical relationship. Second, this paper uses the chance constraint on the resource limitation. We do not strictly limit the consumption of resources. In some cases, exceeding the resource limit can be allowed, as long as the limitation is met in most cases. The chance constraint is a complicated problem. In addition, this problem has many variables, and the system reliability can only be obtained by simulation. We propose an efficient simulation optimization method. A numerical study shows that the proposed method can locate the optimal solution more efficiently compared to the existing methods.

中文摘要..........................................................I
Abstract.........................................................II
目錄............................................................III
圖目錄............................................................V
表目錄...........................................................VI
第一章 緒論.......................................................1
1.1 研究背景與動機........................................1
1.2 研究目的..............................................2
1.3 論文架構..............................................3
第二章 文獻回顧...................................................5
2.1 冗餘配置問題..........................................5
2.2 模擬最佳化............................................9
2.3  Nelder-Mead單形法(Nelder-Mead Simplex Method).......13
第三章 數學模型...................................................15
3.1 問題定義.............................................15
3.2 符號定義.............................................16
3.3 一般化數學模型........................................17
第四章 求解方法...................................................18
4.1 可靠度之估計方法......................................18
4.2 定義信賴區域..........................................20
4.3 決策變數之轉換........................................21
4.4  Nelder-Mead單形法(Nelder-Mead Simplex Method).......21
4.5 成本限制式檢驗........................................25
4.6 鄰域解績效評估........................................25
4.7 延伸找到暫時點........................................31
4.8 更新信賴區域..........................................32
4.9 提出之演算法..........................................33
第五章 數值結果...................................................35
5.1 簡單橋狀系統..........................................35
5.2 複雜網路系統..........................................39
第六章 結論與未來研究.............................................45
6.1 結論.................................................45
6.2 未來研究..............................................45
參考文獻..........................................................46

                                

Ardakan, M. A., and Hamadani, A. Z. (2014). Reliability optimization of series–parallel systems with mixed redundancy strategy in subsystems. Reliability Engineering & System Safety, 130, 132-139.
Box, G. E., and Wilson, K. B. (1951). On the experimental attainment of optimum Conditions. Journal of the Royal Statistical Society. Series B (Methodological), 13(1), 1-45.
Carson, Y., and Maria, A. (1997). Simulation optimization: methods and applications. In Proceedings of the 29th Conference on Winter Simulation, 118-126.
Chern, M. S. (1992). On the computational complexity of reliability redundancy allocation in a series system. Operations Research Letters, 11(5), 309-315.
Coit, D. W., and Smith, A. E. (1996). Reliability optimization of series-parallel systems using a genetic algorithm. IEEE Transactions on Reliability, 45(2), 254-260.
Coit, D. W., and Smith, A. E. (1996). Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Computers & Operations Research, 23(6), 515-526.
Coit, D. W., and Smith, A. E. (1996). Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Computers & Operations Research, 23(6), 515-526.
Dobani, E. R., Ardakan, M. A., Davari-Ardakani, H., and Juybari, M. N. (2019). RRAP-CM: A new reliability-redundancy allocation problem with heterogeneous components. Reliability Engineering & System Safety, 191, 106563.
Zhang E., and Chen Q. (2016). Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization. Reliability Engineering & System Safety, 145, 83-92.
Fyffe, D. E., Hines, W. W., and Lee, N. K. (1968). System reliability allocation and a computational algorithm. IEEE Transactions on Reliability, 17(2), 64-69.
Ghare, P. M., and Taylor, R. E. (1969). Optimal redundancy for reliability in series systems. Operations Research, 17(5), 838-847.
Ha, C., and Kuo, W. (2006). Reliability redundancy allocation: An improved realization for nonconvex nonlinear programming problems. European Journal of Operational Research, 171(1), 24-38.
Gholinezhad, H., and Hamadani, A. Z. (2017). A new model for the redundancy allocation problem with component mixing and mixed redundancy strategy. Reliability Engineering & System Safety, 164, 66-73.
Kim, H., and Kim, P. (2017). Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm. Reliability Engineering & System Safety, 159, 153-160.
Kulturel-Konak, S., Smith, A. E., and Coit, D. W. (2003). Efficiently solving the redundancy allocation problem using tabu search. IIE transactions, 35(6), 515-526.
Liang, Y. C., and Smith, A. E. (2004). An ant colony optimization algorithm for the redundancy allocation problem (RAP). IEEE Transactions on Reliability, 53(3), 417-423.
Lin, J. Y., and Donaghey, C. E. (1993). A Monte Carlo simulation to determine minimal cut sets and system reliability. IEEE Proceedings of the 1993 Annual Reliability and Maintainability Symposium, 246-249.
Mahato, S. K. (2016a) Optimization of Redundancy Allocation Problem with Defuzzified Fuzzy Reliabilities. Imperial Journal of Interdisciplinary Research, 2(2), 266-276.

Mahato, S. K. (2016b) Optimization of System Reliability of an n-Stage Parallel-Series RAP in Precise and Stochastic Environments. Imperial Journal of Interdisciplinary Research, 2(2), 355-343.
Mettas, A. (2000). Reliability allocation and optimization for complex systems. Proceedings of the 2000 Annual Reliability and Maintainability Symposium 216-221.
Misra, K. B., and Sharma, U. (1991). An efficient algorithm to solve integer-programming problems arising in system-reliability design. IEEE Transactions on Reliability, 40(1), 81-91.
Nelson, B. L. (2010). Optimization via simulation over discrete decision variables. Informs Tutorials in Operations Research, 193-207.
Painton, L., and Campbell, J. (1995). Genetic algorithms in optimization of system reliability. IEEE Transactions on Reliability, 44(2), 172- 178.
Ramirez-Marquez, J. E., and Coit, D. W. (2004). A heuristic for solving the redundancy allocation problem for multi-state series-parallel systems. Reliability Engineering & System Safety, 83(3), 341-349.
Yeh, W. C., Lin, Y. C., Chung, Y. Y., and Chih, M. (2010). A particle swarm optimization approach based on Monte Carlo simulation for solving the complex network reliability problem. IEEE Transactions on Reliability, 59(1), 212-221.
Zhao, R., and Liu, B. (2003). Stochastic programming models for general redundancy optimization problems. IEEE Transactions on Reliability, 52(2), 181-191.
Ouyang, Z., Liu, Y., Ruan, S. J., and Jiang, T. (2019). An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and heterogeneous components. Reliability Engineering & System Safety, 181, 62-74.

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