ارائه مدلی کارا برای افزایش قابلیت دسترسی سیستم‌های دارای قطعات تعمیرپذیر و تعمیرناپذیر به صورت چند هدفه مسئله تخصیص اجزای مازاد

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی صنایع، دانشگاه صنعتی اصفهان، اصفهان، ایران

2 دانشیار، دانشکده مهندسی صنایع، دانشگاه امام حسین (ع)، تهران، ایران

چکیده

قابلیت اعتماد و قابلیت دسترسی از جمله مشخصه­های مهم در اکثر سیستم­ها بالاخص سیستم­های الکترونیکی و مکانیکی هستند که در صنایع ارتباطات هوایی، شبکه­های اینترنتی، سیستم­های مخابراتی، سیستم­های تولید نیرو، تسهیلات تولیدی و غیره مطرح می باشند که از جمله مهمترین دلایل آن افزایش پیچیدگی سیستمها، سخت و حساس­تر شدن فضای رقابتی بازار، افزایش هزینه­های تولید در صورت ایجاد توقف و... می­باشد. در این مقاله با الهام از تحقیقات صورت گرفته در زمینه قابلیت اعتماد و بهینه­سازی قابلیت اعتماد سیستم­ها، مدلی با تابع هدف چندگانه ارائه شده که تابع هدف آن شامل بهینه‌سازی قابلیت دسترسی و هزینه کل سیستم­ها، در شرایطی که سیستم شامل هر دو نوع قطعه تعمیرناپذیر و تعمیرپذیر  ‌باشد. در این مدل قابلیت دسترسی سیستم‌ علاوه بر تخصیص اجزای مازاد به زیرسیستم‌ها، تخصیص قابلیت دسترسی برای اجزا نیز در نظر گرفته شده است که این امر باعث افزایش انعطاف­پذیری مدل برای افزایش قابلیت دسترسی سیستم­ها می‌­باشد. برای حل مدل طراحی شده، از الگوریتم ژنتیک مبتنی بر چینش جواب­های ممتاز ناچیره  (NSGA-II) استفاده شده است که دارای توان بالا برای حل چنین مسائلی می­باشد. در پایان نیز برای بیان کارائی مدل پبشنهادی و روش حل آن یک مثال عددی ارائه شده است که در این مثال سیستمی در نظر گرفته شده است که بخشی از اجزاء تشکیل دهنده آن  تعمیرناپذیر و  بخش دیگر  آن تعمیرپذیر می­باشد.

کلیدواژه‌ها

عنوان مقاله [English]

Provide an efficient model to increase the accessibility of systems with repairable and non-repairable parts as a multi-objective problem of allocating surplus components

نویسندگان [English]

  • Hossein Zolfaghari 1
  • Ardeshir Ahmadi 2
1 Faculty of Industrial Engineering, Isfahan University of Technology, Isfahan, Iran
2 Associate Professor, Faculty of Industrial Engineering, Imam Hossein University, Tehran, Iran
چکیده [English]

Reliability and accessibility are important features in most systems, especially electronic and mechanical systems, which are in the industries of air communication, Internet networks, telecommunication systems, power generation systems, production facilities, etc., which are among the most important reasons for increasing the complexity of systems. , Hardening and more sensitive market competitive environment, increasing production costs in the event of a stoppage, and so on. In this paper, inspired by research on the reliability and optimization of systems reliability, a model with multiple objective function is presented, the objective function of which includes accessibility optimization and cost of all systems, where the system includes both non-repairable components and Is repairable. In this model, system accessibility, in addition to allocating surplus components to subsystems, allocation of accessibility for components is also considered, which increases the flexibility of the model to increase the accessibility of systems. To solve the designed model, a genetic algorithm based on the arrangement of non-privileged solutions (NSGA-II) is used, which has a high power to solve such problems. Finally, a numerical example is presented to express the efficiency of the proposed model and the method of solving it. In this example, a system is considered in which part of its components is unrepairable and the other part is repairable.

کلیدواژه‌ها [English]

  • Reliability
  • accessibility
  • Multi-objective model
  • Allocation of accessibility-surplus components
  • Non-repairable parts and repairable parts
  • Genetic algorithm based on the arrangement of insignificant excellent answers

مراجع

[1] Barlow, R. E., & Proschan, F. (1975). Statistical theory of reliability and life testing: probability models. Florida State Univ Tallahassee.‏
[2] Hamadani, A.Z. "Availability and Reliability Modeling", Ph.D. dissertation, University of Bradford, England, .
[3] Chern, M. S. (1992). On the computational complexity of reliability redundancy allocation in a series system. Operations research letters, 11(5), 309-315.‏
[4] Coit, D. W., & Smith, A. E. (1996). Penalty guided genetic search for reliability design optimization. Computers & industrial engineering, 30(4), 895-904.
[5] Elegbede, C., & Adjallah, K. (2003). Availability allocation to repairable systems with genetic algorithms: a multi-objective formulation. Reliability Engineering & System Safety, 82(3), 319-330.‏
[6] Marseguerra, M., Zio, E., & Podofillini, L. (2004). Optimal reliability/availability of uncertain systems via multi-objective genetic algorithms. IEEE Transactions on Reliability, 53(3), 424-434.‏
[7] Meziane, R., Massim, Y., Zeblah, A., Ghoraf, A., & Rahli, R. (2005). Reliability optimization using ant colony algorithm under performance and cost constraints. Electric power systems research, 76(1), 1-8.‏
[8] Chen, W.," Optimal apportionment of reliability and redundancy in series systems under multiple objectives ". Applied Mathematics and Computation,vol.175(2),pp.1412-1423,2006.
[9] Chiang, C. H., & Chen, L. H. (2007). Availability allocation and multi-objective optimization for parallel–series systems. European journal of operational research, 180(3), 1231-1244.‏
[10] dos Santos Coelho, L. (2009). An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications. Reliability Engineering & System Safety, 94(4), 830-837.‏
[11] Wu, P., Gao, L., Zou, D., & Li, S. (2011). An improved particle swarm optimization algorithm for reliability problems. ISA transactions, 50(1), 71-81.‏
[12] Zou, D., Gao, L., Li, S., & Wu, J. (2011). An effective global harmony search algorithm for reliability problems. Expert Systems with Applications, 38(4), 4642-4648.‏
[13] Wang, L., & Li, L. P. (2012). A coevolutionary differential evolution with harmony search for reliability–redundancy optimization. Expert Systems with Applications, 39(5), 5271-5278.‏
[14] Tan, Y., Tan, G. Z., & Deng, S. G. (2013). Hybrid particle swarm optimization with differential evolution and chaotic local search to solve reliability-redundancy allocation problems. Journal of Central South University, 20, 1572-1581.‏
[15] Zoulfaghari, H., Hamadani, A. Z., & Ardakan, M. A. (2014). Bi-objective redundancy allocation problem for a system with mixed repairable and non-repairable components. ISA transactions, 53(1), 17-24.‏
[16] Soltani, R., Safari, J., & Sadjadi, S. J. (2015). Robust counterpart optimization for the redundancy allocation problem in series-parallel systems with component mixing under uncertainty. Applied Mathematics and Computation,271, 80-88.‏
[17] Zhang, E., & Chen, Q. (2016). Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization. Reliability Engineering & System Safety, 145, 83-92.‏
[18] Fyffe, D. E., Hines, W. W., & Lee, N. K. (1968). System reliability allocation and a computational algorithm. IEEE Transactions on Reliability, 2, 64-69.‏
[19] Deb, K., Agrawal, S., Pratap, A., & Meyarivan, T. (2000, September). A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In International Conference on Parallel Problem Solving From Nature (pp. 849-858). Springer Berlin Heidelberg.‏
[20] Zarabian, M., Niaki, S. T. A., & Mehrabad, M. S. A NSGA-II algorithm to solve a bi-objective optimization of the redundancy allocation problem for series-parallel systems.‏
[21] Sadeghi, J., Sadeghi, S., & Niaki, S. T. A. (2014). A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: An NSGA-II with tuned parameters. Computers & Operations Research, 41, 53-64.‏
[22] Pourkarim Guilani, P. (2016). Using NSGA II Algorithm for a Three Objectives Redundancy Allocation Problem with k-out-of-n Sub-Systems. Journal of Optimization in Industrial Engineering, 9(19), 87-96.‏
[23] Zou, D., Gao, L., Li, S., & Wu, J. (2011). An effective global harmony search algorithm for reliability problems. Expert Systems with Applications, 38(4), 4642-4648.‏
 [24] Ebrahimipour, V., & Sheikhalishahi, M. (2011, April). Application of multi-objective particle swarm optimization to solve a fuzzy multi-objective reliability redundancy allocation problem. In Systems Conference (SysCon), 2011 IEEE International (pp. 326-333). IEEE.‏
نشریه علمی پژوهشی مهندسی و مدیریت کیفیت
دوره 6، شماره 3
آبان 1395
صفحه 191-203

فایل ها

هم رسانی

ارجاع به این مقاله

آمار