reliability redundancy allocation problem
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امروزه با پیچیده تر شدن سیستم ها مفهوم قابلیت اطمینان و بهینه سازی مورد پژوهش و بررسی قرار گرفته است. در مراحل اولیه ی طراحی سیستم بسیاری از ویژگی های سیستم عدم قطعیت همراه است. از ان جا که استفاده از رویکرد احتمالی در حل مسائل قابلیت اطمینان دارای محدودیت هایی است و لذا استفاده از رویکرد فازی برای حل مسائل بهینه سازی قابلیت اطمینان بسیار کاراتر است. یکی از راه های بهینه سازی قابلیت اطمینان تخصیص افزونگی است. در پژوهش حاضر، مساله ی تخصیص قابلیت اطمینان - افزونگی با دو استراتژی فعال و استراتژی ذخیره- سرد با رویکرد اعداد فازی مثلثی در استفاده از پارامترهای توابع خرابی و محاسبه ی قابلیت اطمینان مورد بررسی قرار گرفته است. برای حل مساله ی فوق از الگوریتم ژنتیک استفاده گردیده است. نتایج حاصل با نتایج حاصل از حل به روش دقیق مقایسه شده و از نتایج حاصل از حل مدل قطعی بسیار کاراتر است.
کلید واژگان: : مساله تخصیص قابلیت اطمینان- افزونگی، اعداد فازی مثلثی، الگوریتم ژنتیک، استراتژی فعال، استراتژی ذخیره-سردapplication of Reliability can be seen in many industrial, communication, In the early stages of system design, many system features such as reliability, weight, cost, and etc are associated with uncertainty due to various reasons such as lifespan, operational conditions, etc. Since the use of the probabilistic approach in solving reliability problems has limitations and can only be used in quantitative analysis of information and in many cases does not produce useful and sufficient results for experts, therefore the use of the approach Fuzzy is much more efficient for solving reliability optimization problems. One of the ways to optimize the reliability is to allocate redundancy. When using redundant components in a subsystem, how the redundant components are used is particular importance. In reliability-redundancy allocation problems, the reliability of components is not known in advance and is considered as a decision variable. In the current research, the reliability-redundancy allocation problem has been investigated with two active and cold-standby redundancy strategies and the triangular fuzzy number approach has been used in using the parameters of probability functions and reliability calculation in two model problems and an industrial system. Genetic algorithm has been used to solve the problem. In the implementation of the genetic algorithm, the the random, tournament and roulette wheel methods has been used to select parents and different types of mutation and crossover operators have been used to produce children. The results are more efficient than the results obtained from solving the deterministic model.
Keywords: Reliability-redundancy Allocation Problem, triangular fuzzy numbers, Genetic Algorithm, active strategy, cold -standby strategy -
In some reliability optimization problem the constraints relations have probabilistic nature. These constraints are called the chance constraints and are difficult to handle up to some extent. The aim of this paper is to solve the reliability-redundancy allocation problem involving chance constraints in precise and imprecise environments. The component reliabilities of the system are imprecise numbers and further the constraints are stochastic type i.e., chance constraints. The genetic algorithm incorporated with stochastic simulation approach is implemented to optimize the system reliability. We introduced the fuzzy and intuitionistic fuzzy numbers to consider the impreciseness. In particular, component reliabilities are assumed to be triangular fuzzy numbers and triangular intuitionistic fuzzy numbers in two different environments. The simulation technique known as Monte Carlo Simulation is used to find the deterministic constraints from the stochastic ones. To transform the constrained optimization problem into unconstrained one we make use of the effective Big-M penalty approach. The problems are coded with real coded genetic algorithm. We have taken up some numerical examples to show the performance of the proposed method and the sensitivities of the GA parameters are also presented graphically.Keywords: Reliability-redundancy Allocation Problem, Fuzzy number, intuitionistic fuzzy numbers, Real Coded Genetic Algorithm, chance constraint, Stochastic simulation technique
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International Journal of Supply and Operations Management, Volume:5 Issue: 3, Spring 2018, PP 218 -233
Reliability-redundancy allocation problem (RRAP) is one of the most practical methods used to improve system reliability through performing a tradeoff between reliability and redundancy levels of components. RRAP aims to maximize the overall system reliability by creating a balance between the reliabilities of components and the number of redundant components in each subsystem. In RRAP, redundant components operate in a predetermined order under a redundancy strategy. In this paper, cold standby redundancy strategy is considered for the redundant components. Besides, a penalty guided water cycle algorithm is adjusted for solving the problem. The proposed algorithm is implemented on two famous benchmark problems to evaluate the performance of the proposed approach. Numerical results reveal the superiority of the proposed solution method compared to previous studies.
Keywords: Reliability-redundancy allocation problem, Cold-standby strategy, Reliability optimization, Water cycle algorithm
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