[1] Groover
M. P. (2010). Fundamentals of Modern Manufacturing: Materials, Processes, and Systems. John Wiley & Sons.
[2] A.K. Tsadiras, C.T. Papadopoulos, M.E.J. O’Kelly. An artificial neural network based decision support system for solving the buffer allocation problem in reliable production lines. Computers & Industrial Engineering 66 (2013) 1150–1162.
[3]
Mariano C.H and Pece
C.A.Z. (2015). Simulation Optimization Approach to Solve a Complex Multi-objective Redundancy Allocation Problem. Applied Simulation and Optimization, Springer Cham Heidelberg, Newyork.
[4] Yelkenci Kose, S., & Kilincci, O. (2015). Hybrid approach for buffer allocation in open serial production lines, Computers & Operations Research. Computers and Operations Research; 60(c):67-78.
[6] Gershwin, S. B., & Schor, J. E. (2000). Efficient algorithms for buffer space allocation. Annals of Operations Research, (93), 117–144.
[7] Manitz, M. (2008). Queuing model based analysis of assembly lines with finite buffers and general services times. Comput Oper Res, 35(8), 2520–2536.
[8] Amiri, M., & Mohtashami, A. (2012). Buffer allocation in unreliable production lines based on design of experiments, simulation, and genetic algorithm. Int J Adv Manuf Technol,(62), 371–383.
[9] Costa, A., Alfieri, A., & Fichera, S. (2015). A parallel tabu search for solving the primal buffer allocation problem in serial production systems, Computers & Operations Research, (64):97-112.
[10] امیری, مقصود و علی محتشمی، ۱۳۹۳، حداکثر کردن نرخ تولید از طریق تعیین اندازه بهینه موجودی های بافر با استفاده از رویکرد تلفیقی متدولوژی سطح پاسخ و الگوریتم ژنتیک، فصلنامه بین المللی مهندسی صنایع و مدیریت تولید 25 (2).167-184.
[11] Chern, M. S. (1992). On the computational complexity of reliability redundancy allocation in a series system. Oper Res Lett, (11), 309–315.
[12] Ida, K., Gen, M. and Yokota, T. (1994). System Reliability Optimization with Several Failure Modes by Genetic Algorithm, Proceeding of the 16th International Conference on Computers and Industrial Engineering, Ashikaga of Japan,82.
[13] Yokota, T., Gen, M. and Ida, K. (1995). System Reliability of Optimization Problems with Several Failure Modes by Genetic Algorithm, Japanese Journal of Fuzzy Theory and systems.; Vol. 7, pp. 117-135.
[14] Tavakkoli-Moghaddam, R., Safari, J., Sassani, F. (2008). Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm. Reliability Engineering & System Safety, 93 (4), 550-556.
[15] Chambari, A., Rahmati, S.H., Najafi A.A., & Karimi, A. (2012). A bi-objective model to optimize reliability and cost of system with a choice of redundancy strategies. Computers & Industrial Engineering, 63(1):109–119.
[16] Jiansheng G., Zutong, W., Mingfa, Z., Ying, W. (2014).Uncertain multi-objective redundancy allocation problem of repairable systems based on artificial bee colony algorithm. Chinese Journal of Aeronautics, 27(6): 1477–1487.
[17] Zoulfaghari, H., Zeinal Hamadani, A., & Abouei Ardakan, M. (2014). Bi-objective redundancy allocation problem for a system with mixed repairable and non-repairable components. ISA Transactions. 53: 17–24.
[18] Abouei Ardakan, M., Zeinal Hamadani, A. & Alinaghian, M. (2015). Optimizing bi-objective redundancy allocation problem with a mixed redundancy strategy. ISA Transactions; 55; 116–128.
[19] Kayedpour, F., Amiri, A., Rafizadeh, M., & ShahryariNia, A. (2016). Multi-objective redundancy allocation problem for a system with repairable components considering instantaneous availability and strategy selection. Reliability Engineering & System Safety, 160.132-151.
[20] Heydari M and Sullivan KM. (2018). An Integrated Approach to Redundancy Allocation and Test Planning for Reliability Growth.Computers & Operations Research. 92, 182-193.
[21] محتشمی، علی. یک روش تلفیقی جدید جهت تخصیص افزونگی در سیستمهای تولیدی با استفاده از اصلاحشدهMOPSO وNSGA-II . فصلنامه علمی پژوهشی مطالعات مدیریت صنعتی، سال دوازدهم، شماره 33، تابستان 1393.صفحات 97 – 124.
[22] شریفی، مانی؛ دشتی ملجائی، کامران و چراغی، قاسم(1395). بهینهسازی همزمان قابلیت اطمینان و هزینهی طراحی در سیستمهای سری ـ موازی k-out-of-n با در نظرگرفتن نرخ خرابی وابسته به تعداد اجزای در حال کار. مهندسی صنایع و مدیریت، دوره 32(1)، شماره 2(1)، 141-148.
[23] عزیزمحمدی ،روزبه؛ امیری،مقصود؛ توکلی مقدم، رضا و مشاط زادگان، حمیدرضا.ارائه مدلی برای حل مسئله تخصیص افزونگی قابلیت اطمینان بهوسیله یک الگوریتم رقابتی تلفیقی چندهدفه. فصلنامه علمی پژوهشی مطالعات مدیریت صنعتی، سال چهاردهم، شماره ،42، پاییز 1395، صفحات 103 تا 121.
[24] عظیمی، پرهام و هادی نژاد، فرهاد.(1395). ارائه مدل بهینه سازی چند هدفه در مساله تخصیص افزونگی سیستم- های تعمیرپذیر، با بهره گیری از تکنیک های تصمیم گیری چند معیاره، طراحی آزمایشات و شبیه سازی.مطالعات مدیریت صنعتی، دوره 14، شماره 41، 137-165.
[25] فاروقی، هیوا و سلگی، زهرا.(1396). بهینهسازی مسئله چند هدفه تخصیص افزونگی و قابلیت اطمینان در سیستمهای چند وضعیته سری- موازی، مهندسی و مدیریت کیفیت، دوره 7، شماره 3، ، 176-185.
[26] Alrabghi, A., & Tiwari, A. (2016). A novel approach for modeling complex maintenance systems using discrete event simulation. Reliability Engineering and System Safety, 154, 160–170.
[27] Rigdon S.E & Basu A.P.(2000). Statistical Methods for the Reliability of Repairable Systems.Wiley series in probability and statistics.
[28] Stenström, C., Parida, A., & Kumar, U. (2016). Measuring and monitoring operational availability of rail infrastructure. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 230(5), 1457–1468.
[29] Yahyatabar A., & Najafi A.A.(2016). A quadratic reproduction based Invasive Weed Optimization algorithm to minimize periodic preventive maintenance cost for series-parallel systems. Computers & Industrial Engineering.v(110), 436-461.
[30] M.Okasha
Nader & M.Frangopol
Dan Lifetime-oriented multi-objective optimization of structural maintenance considering system reliability, redundancy and life-cycle cost using GA.
Structural Safety V(31), I(6), 460-474.
[31] Zheng, Z., Zhou, W., Zheng, Y., & Wu, Y. (2016). Optimal maintenance policy for a system with preventive repair and two types of failures, Computers & Industrial Engineering. 98:102-112.
[32]ربانی، علی؛ زارع، حبیب و بهنیا، فروغ.(1392) .ارائه الگوی مناسب جهت پیاده سازی سیستم نگهداری و تعمیرات در کارخانجات خطوط تولید پیوسته با رویکرد مدل های تصمیم گیری و برنامه ریزی آرمانی فازی. فصلنامه علمی – پژوهشی مطالعات مدیریت صنعتی – سال یازدهم، شماره 31 ، صفحات 85-100.
[33]ربانی، مسعود؛ افرازه، محمدحسین؛ امینی، ساسان؛ فرخی اصل، حامد.(1395). برنامه ریزی یکپارچه تولید و نگهداری و تعمیرات با درنظر گرفتن دورههای یکسان نت. روشهای عددی در مهندسی، سال 36 ،شمارة 2 ، صفحات 63-78.
[33] Mohtashami, A. (2014). A new hybrid method for buffer sizing and machine allocation in unreliable production and assembly lines with general distribution time-dependent parameters. Int J Adv Manuf Technol. 74:1577–1593.
[34] P. Pourkarim Guilani, P. Azimi, S.T.A. Niaki, S.A. Akhavan Niaki. (2016). Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach. Reliability Engineering and System Safety. 152;187–196.
[35] Attar, A., Raissi, S., & Khalili-Damghani, K. (2017). A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems. Reliability Engineering and System Safety,157, 177–191.
[36] Lavoie
Ph., Jean-Pierre,
K. & Gharbi, A. (2009).Optimization of production control policies in failure-prone homogenous transfer lines. IIE Transactions 41(3):209-222.
[37] Montgomery,
D.C. (2012). Design and Analysis of Experiments, 8
th Edition, Wiley.
[38] Esfe,
M. H., Razi,
P., Hajmohammad,
M. H., Rostamian,
S. H., Sami Sarsam,
W., Akbar Abbasian Arani,
A., & Dahari,
M. (2017). Optimization, modeling and accurate prediction of thermal conductivity and dynamic viscosity of stabilized ethylene glycol and water mixture Al2O3 nanofluids by NSGA-II using ANN.
International Communications in Heat and Mass Transfer,
82, 154-160.
[39] Huang, M., Guang, C., Pao, L., & Chou, Y. (2002). Buffer allocation in flow shop-type production system with general arrival and service patterns. Comput Oper Res, 29(2), 103–121.
[40] Deb, K.(2002). A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II. IEEE Transaction on Evolutionary Computation, VOL. 6, NO. 2.182-197.
[41] Coello Coello C.A., Lamont G.B. & Van Veldhuizen D.A. (2007). Evolutionary Algorithms for Solving Multi-Objective Problems. Second Edition. Springer Science & Business Media.
[42] Pasandideh, S.H.R., Akhavan Niaki, S.T., & Asadi, K. (2015). Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Science, 292, 57–74.
[43] Pierreval
H., & Durieux
S .(2003).Robust simulation with a base environmental scenario. European Journal of Operational Research 182(2):783-793
[44] Chang, Kuo-Hao., & Kuo P.Y. (2018). An efficient simulation optimization method for the generalized redundancy allocation problem.