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جستجوی مقالات مرتبط با کلیدواژه

redundancy allocation problem

در نشریات گروه فنی و مهندسی
  • Pardis Roozkhosh, Amirmohammad Fakoor Saghih*

    The reliability of each component in a system plays a crucial role, as any malfunction can significantly reduce the system's overall lifespan. Optimizing the arrangement and sequence of heterogeneous components with varying lifespans is essential for enhancing system stability. This paper addresses the redundancy allocation problem (RAP) by determining the optimal number of components in each subsystem, considering their sequence, and optimizing multiple criteria such as reliability, cost uncertainty, and weight. A novel approach is introduced, incorporating a switching mechanism that accommodates both correct and defective switches. To assess reliability benefits, Markov chains are employed, while cost uncertainty is evaluated using the Monte-Carlo method with risk criteria such as percentile and mean-variance. The problem is solved using a modified genetic algorithm, and the proposed method is benchmarked against alternative approaches in similar scenarios. The results demonstrate a significant improvement in the Model Performance Index (MPI), with the best RAPMC solution under a mixed strategy achieving an MPI of 0.98625, indicating superior model efficiency compared to previous studies. Sensitivity analysis reveals that lower percentiles in the cost evaluations correlate with reduced objective function values and mean-variance, confirming the model's robustness in managing redundancy allocation to optimize reliability and control cost uncertainties effectively.

    Keywords: Redundancy Allocation Problem, Repairable, Component Sequencing, Markov Chain, Mixed Strategy, Cold Standby
  • Mani Sharifi *

    In this paper, we study a redundancy allocation problem. The investigated problem has a system with s serially connected subsystems, which are under periodic inspection. In each subsystem, component failures are diagnosed by a perfect switching system, and the first component on the standby queue starts working as a replacement for the failed component. . The failures of the components are detected at inspection. The failed component(s) will be repaired during the next inspection interval and added to the standby queue. The subsystems can be in different states depending on their working component and the order of the components on the standby queue. We present an approach to calculate the subsystems-states transition probabilities. We used a two-phase approach to minimize the system cost. In the first phase, we minimize the subsystem's expected total cost by determining the optimal number of components and the optimal subsystem's inspection intervals. The expected total cost consists of downtime, repair, and inspection costs of the subsystems per unit time. Then, in the second phase, we determine the optimum allocated components to each subsystem under some constraints to find the optimal system inspection cost per unit time

    Keywords: Redundancy Allocation Problem, Periodic Inspection, Inspection Interval, Transition Probabilities, Standby Configuration, Markov Theory
  • M. Sharifi *, M. Shahriyari, A. Khajehpoor, S. A. Mirtaheri
    In this research, a new hybrid model for the redundancy allocation problem (RAP) in a series-parallel configuration with the k-out-of-n subsystem is presented. In the given model, the redundancy policy is set to an active, warm standby, or no redundancy. In warm standby policy, an imperfect switch detected the component's failure and replaced the fail component with a new standby one. So, the subsystems' redundancy policy is one of the model's decision variables. We presented a new objective function for the RAP to calculate the reliability of a system that consists of active and warm standby subsystems. The presented model aims to determine the subsystems' redundancy policy, the type and number of redundant components to maximize the system's reliability, under the system's cost, volume, and weight constraints. To solve the proposed model, we used two Genetic Algorithm (GA) and hybrid GA (HGA) meta-heuristic algorithm with local search. Since the %RPD of HGA is 2.1% (on average) better than GA in solving ten large-scale instances, the result shows the superiority of HGA in comparison with GA for solving the presented RAP.
    Keywords: Redundancy allocation problem, warm standby, Reliability, Meta-heuristic methods
  • M. Sharifi *, Gh. Cheragh, K. Dashti Maljaii, A. Zaretalab, M. Shahriari
    This paper presents a new redundancy allocation problem for a system with the k-out-of-n configuration at the subsystems’ level with two active and cold standby redundancy strategies. The failure rate of components in each subsystem depends on the number of working components. The components are non-reparable, and the failure rate of the component can be decreased with some preventive maintenance actions. The model has two objective functions: maximizing the system’s reliability and minimizing the system’s costs. The system aims to find the type and number of components in each subsystem, redundancy strategy of subsystems, as well as the decreased values of components failure rates in subsystems. Since the redundancy allocation problem belongs to NP-Hard problems, two Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Non-Dominated Ranked genetic algorithm (NRGA) metaheuristic algorithms were used to solve the presented model and to tune algorithms parameters we used response surface methodology (RSM). Besides, these algorithms were compared using five different performance metrics. Finally, the hypothesis test was used to analyze the results of the algorithms.
    Keywords: Reliability, Redundancy allocation problem, NSGA-II, NRGA, Response Surface Methodology
  • مصطفی ابویی اردکان*، سجاد تلخابی

    یکی از روش های رایج برای بهبود قابلیت اطمینان، استفاده از قطعات مازاد موازی در زیرسیستم ها است. این مسئله که تحت عنوان مسئله تخصیص افزونگی شناخته می شود، شامل انتخاب اجزای مازاد جهت حداکثر کردن قابلیت اطمینان سیستم با توجه به محدودیت های از پیش تعیین شده ای نظیر هزینه، وزن و حجم سیستم است. به طور سنتی دو استراتژی قطعات مازاد فعال و ذخیره برای حل این گونه مسایل وجود دارد. به تازگی استراتژی جدیدی تحت عنوان استراتژی مختلط ارایه شده است که عملکرد بهتری نسبت به هر دو استراتژی قبلی داشته است. مشکلی اصلی در استفاده از استراتژی مختلط، پیچیدگی معادلات مربوط به آن است. از این رو، در این مقاله یک روش جدید برای محاسبه قابلیت اطمینان استراتژی مختلط ارایه می شود که نیازی به محاسبات پیچیده انتگرالی روش قبل را ندارد و همچنین باعث کاهش زمان حل مسایل می شود. روش حل پیشنهادی به کمک روابط بازگشتی، یک حالت کلی از فرمول استراتژی مختلط ارایه می دهد که با افزایش یا کاهش قطعات هر زیرسیستم، فرمول محاسباتی تغییر چندانی نمی کند. این انعطاف پذیری و ثبات در فرمول، در سیستم هایی با تعداد قطعات بالا، بسیار کارآمد خواهد بود. به منظور ارزیابی روش حل جدید و مقایسه آن با روش پیشین، مسئله الگوی سری- موازی با چهارده زیرسیستم در نظر گرفته شده و نتایج دو روش با یکدیگر مقایسه شده است.

    کلید واژگان: بهینه سازی قابلیت اطمینان، تخصیص افزونگی، استراتژی مختلط، توابع بازگشتی
    M. Abouei Ardakan*, S. Talkhabi

    One of the common approaches for improving the reliability of a specific system is to use parallel redundant components in subsystems. This approach, which is known as the redundancy allocation problem (RAP), includes the simultaneous selection of the component type and its level for each subsystem in order to maximize the system reliability.Traditionally, there are two redundancy strategies, namely active and standby, for the redundant components. Recently, a new powerful strategy called mixed strategy has been developed. It has been proved that the mixed strategy has a better performance when compared to both previous strategies. The main issue in utilizing the mixed strategy is its complicated formulation and sophisticated calculations, leading to a time-consuming procedure for solving the problems. Hence, in this paper, a new formulation based on the recursive approach is introduced to ease the calculation of the mixed strategy. In the new formulation, the complex double integral calculations are removed and the calculation times is reduced. The proposed recursive formulation provides a general statement for the mixed strategy formula which is not changed by altering the number of components in each subsystem. This flexibility and stability in the formula can be very important, especially for large scale cases. In order to evaluate the new approach and to compare its performances with the previous formulation, a benchmark problem with 14 subsystems is considered and the results of the two formulation are compared with each other.

    Keywords: Reliability optimization, Redundancy allocation problem, Mixed strategy, Recursive functions
  • عبدالصابر پیروی، مهدی کرباسیان *، مصطفی ابویی اردکان

    یکی از روش های رایج در بهینه سازی قابلیت اطمینان، استفاده از اجزای مازاد موازی در زیرسیستم هاست. این مسئله که با عنوان مسئله ی تخصیص اجزای مازاد شناخته می شود، شامل انتخاب اجزای مازاد به منظور بیشینه کردن قابلیت اطمینان سیستم با توجه به محدودیت های از پیش تعیین شده یی نظیر هزینه، وزن و حجم سیستم است. به تازگی راهبرد جدیدی با عنوان راهبرد مختلط ارائه شده است. در این مقاله حالت کلی تری از راهبرد مختلط با عنوان راهبرد مختلط - هم زمان پیشنهاد شده است. راهبرد پیشنهادی تعمیمی از راهبرد مختلط است که تلاش می کند تعداد دفعات استفاده از سوییچ را کاهش دهد و در نتیجه قابلیت اطمینان را بهبود بخشد. به منظور ارزیابی راهبرد جدید و مقایسه ی آن با راهبردهای پیشین و با توجه به پیچیدگی فرمول های راهبرد جدید، یک زیرسیستم با پنج قطعه در نظر گرفته شده و قابلیت اطمینان آن با استفاده از راهبردهای متفاوت بررسی و با راهبرد پیشنهادی مقایسه شده است.

    کلید واژگان: بهینه سازی قابلیت اطمینان، تخصیص اجزای مازاد، راهبرد مختلط - هم زمان، انتخاب راهبرد
    A. Peiravi, M. Karbasian *, M. Abouei Ardakan

    System reliability optimization is one of practical issue in design and engineering. Adding parallel redundant component is a common approach in order to improve the reliability of a specific system. This approach that is known as redundancy allocation problem (RAP), includes discrete component choices with known characteristics such as reliability, cost, weight in order to maximize system reliability. In RAPs, redundancy strategy plays a significant role in increasing reliability of a system or subsystem. Generally, there are three types of redundancy strategies, namely, active, standby and mixed. The latter is a new strategy which is a combination of the two former and have had some noticeable results. This paper presents a new redundancy strategy for system reliability optimization which is called Sync-Mixed. The proposed strategy is a general form of a recently introduced strategy called "Mixed Strategy" that effort to decrease number of switching system usages. In order to evaluate the efficiency of the Sync-Mixed strategy with regarding complexity of formulas for new strategy, a single specific subsystem with five components will be used and reliability of the subsystem will be computed by considering all three previous strategies and the new one. In previous studies, some well-known benchmark problems, including series system, series-parallel system, parallel-series system, and complex system, have been taken into account. The performances of all strategies are compared byconsidering different values of switching and components reliabilities. In RAP, it is assumed that the switch reliability and components reliability are predetermined parameters. However, in this study different combinations of components reliability and switching system reliability are taken into consideration. The main objective is to evaluate the performance of the new strategy compared to traditional strategies in different situations. Obviously, the subsystem reliability has a direct relationship with the components reliability, switch reliability and type of redundancy strategy. This study is an attempt to shed light on the sensitivity of subsystem reliability as a result of switch and component reliability changes in all redundancy strategies.

    Keywords: Reliability optimization, redundancy allocation problem, Sync-Mixed redundancy strategy, choice of strategy
  • Pedram Pourkarim Guilani, Parham Azimi *, Mani Sharifi, Maghsoud Amiri
    Reliability improvement for electronics and mechanical systems is vital for engineers in order to design of these systems. For this reason, there are many researches in this scope to help engineers in real world applications. One of the useful methods in reliability optimization is redundancy allocation problem (RAP). In the most previous works, the failure rates of system components are considered to be constant based on negative exponential distribution; whereas, nearly all systems in real world have components with time-dependent failure rates; i.e., the failure rates of system components will be changed time by time. In this paper, we have worked on a RAP for a system under k-out-of-n subsystems with time-dependent components failure rates based on Weibull distribution. Also, the redundancy policy of the proposed system is considered as mixed strategy and the optimization method was based on the simulation technique to obtain reliability function as implicit function. Finally, a branch and bound algorithm has been used to solve the model, exactly.
    Keywords: Reliability, Redundancy allocation problem, Weibull Distribution, Time-dependent Failure Rates, Optimization via Simulation
  • طه حسین حجازی*، محسن باقری، حانیه جمشیدی
    امروزه طراحی و به کارگیری سیستم هایی با خصوصیات برتر و قابلیت اطمینان بالاتر برای مهندسان و کاربران، اصلی اساسی به شمار می رود؛ زیرا توجه به این مسئله در استفاده مناسب از یک سیستم در طول دوره عمر آن تاثیرگذار است، همچنین در دنیای رقابتی امروز عرضه سیستمی با هزینه تمام شده کمتر به طوری که قابلیت اطمینان زیاد برای آن حفظ شود، شرکت را در میان مشتریان محبوب می کند. هرچند در سال های اخیر پژوهش هایی در زمینه بهینه سازی پایایی با درنظرگرفتن تخفیفات کلی برای اجزای یک سیستم ارائه شده، نوآوری این تحقیق در آن است که نه تنها راهبرد مازاد فعال، بلکه ترکیبی از اجزا با راهبرد مازاد فعال یا آماده به کار سرد را می توان در یک سیستم به کار برد، به گونه ای که تخفیفات کلی به مجموع اجزاء با دو راهبرد مذکور تعلق بگیرد. علاوه بر این، به منظور نزدیک ترکردن شرایط مسئله به دنیای واقعی، پارامترهای نرخ خرابی و هزینه به صورت غیرقطعی درنظر گرفته شده است که برای حل دو مدل با اهداف حداکثرسازی پایایی و حداقل سازی هزینه به ترتیب رویکرد محدودیت احتمالی بر روی محدودیت مربوط به هزینه و پایایی استفاده می شود. مدل ارائه شده با روش دقیق و با استفاده از نرم افزار GAMS حل شده که با توجه به رفتار مناسب آن در تغییر عوامل موثر در مسئله مورد بررسی نتیجه می گیریم که می توان از این مدل به منظور بهینه سازی پایایی و حداقل سازی هزینه در صنایع تولیدی با تولیدات بالا که به کارگیری سیاست تخفیفات کلی مزیتی را برای آن ها دارد، بهره برداری کرد.
    کلید واژگان: برنامه ریزی احتمالی، تخفیفات کلی، پایایی، سیستم سری- موازی، مسئله تخصیص مازاد
    Taha Hossein Hejazi *, Mohsen Bagheri, Hanieh Jamshidi
    Nowadays, designing and implementing the systems with premier features and higher reliability is deemed to be a basic principle for the engineers and users, because regarding this point can result in the proper use of a system during its lifetime. In today’s competitive world, offering a system with lower total expense, given that its high reliability is maintained, can make the company popular with the customers. In the current research, regarding the discounts based on the total number of the orders, a compound of components with active redundancy strategy and ready to work is determined, in such a way that the cost of purchasing the components is minimized, besides optimizing the whole system’s reliability.In the research, the probable approach in invention can be defined that two models examined with cost minimization and Reliability maximization aims that they are, respectively, the probable restrictions on the cost and Reliability. With regard to the model’s proper treatment of changes in effective factors proposed in the model, it is concluded that this model is exploitable for optimizing stability in mass production industries where applying the global discount policy leads to some benefits.
    Keywords: Chance Constrained Programming, Reliability, Series-parallel system, All unit discount, Redundancy Allocation Problem
  • Pedram Pourkarim Guilani, Arash Zaretalab, S.T. A. Niaki, Pardis Pourkarim Guilani
    Redundancy allocation problem (RAP) is one way to increase system reliability. In most of the models developed so far for the RAP, system components are considered to have a binary state consisting of «working perfect» or «completely failed.» However, to suit real-world applications, this assumption has been relaxed in this paper such that components can have three states. Moreover, a bi-objective RAP (BORAP) is modeled for a system with serial subsystems, in which non-repairable tri-state components of each subsystem are configured in parallel and the subsystem works under the k-out-of-n policy. Furthermore, to enhance system reliability, technical and organizational activities that can affect failure rates of the components and hence can improve the system performance are also taken into account. The aim is to find the optimum number of redundant components in each subsystem such that the system reliability is maximized while the cost is minimized within some real-world constraints. In order to solve the complicated NP-hard problem at hand, the multi-objective strength Pareto evolutionary algorithm (SPEA-II) is employed. As there is no benchmark available, the non-dominated sorting genetic algorithm (NSGA-II) is used to validate the results obtained. Finally, the performances of the algorithms are analyzed using 20 test problems.
    Keywords: Reliability, Redundancy allocation problem, Tri, state components, Bi, objective optimization, SPEA, II
  • P. Azimi, M. Hemmati, A. Chambari
    In this article, a new model and a novel solving method are provided to address the non-exponential redundancy allocation problem in series-parallel k-out-of-n systems with repairable components based on Optimization Via Simulation (OVS) technique. Despite the previous studies, in this model, the failure and repair times of each component were considered to have non-negative exponential distributions. This assumption makes the model closer to the reality where the majority of used components have greater chance to face a breakdown in comparison to new ones. The main objective of this research is the optimization of Mean Time to the First Failure (MTTFF) of the system via allocating the best redundant components to each subsystem. Since this objective function of the problem could not be explicitly mentioned, the simulation technique was applied to model the problem, and di erent experimental designs were produced using DOE methods. To solve the problem, some meta-Heuristic Algorithms were integrated with the simulation method. Several experiments were carried out to test the proposed approach; as a result, the proposed approach is much more real than previous models, and the near optimum solutions are also promising.
    Keywords: Redundancy allocation problem, k, out, of, n systems, Meta, heuristic algorithms, Simulation methods, Enterprise Dynamic (ED) software
  • Meisam Sadeghi, Emad Roghanian *, Hamid Shahriari
    In modeling a cold standby redundancy allocation problem (RAP) with imperfect switching mechanism, deriving a closed form version of a system reliability is too difficult. A convenient lower bound on system reliability is proposed and this approximation is widely used as a part of objective function for a system reliability maximization problem in the literature. Considering this lower bound does not necessarily lead to an optimal solution. In this study by assuming that working time of switching mechanism is exponentially distributed, exact value of system reliability is derived analytically through applying Markov process and solving a relevant set of differential-difference equations. The Runge-Kutta numerical scheme is also employed to verify the accuracy of the results. It is assumed that components time to failure follow an Erlang distribution which is appropriate for most engineering design problems by giving the possibility of modeling different increasing hazard functions. A new mathematical model is presented and its performance is evaluated through solving a well-known example in the literature. Results demonstrate that a higher level of system reliability is achievable through implementing the proposed model.
    Keywords: Cold standby, Redundancy allocation problem, System reliability, Markov process, Differential-difference equations
  • Mahsa Aghaei, Ali Zeinal Hamadani, Mostafa Abouei Ardakan

    To increase the reliability of a specific system, using redundant components is a common method which is called redundancy allocation problem (RAP). Some of the RAP studies have focused on k-out-of-n systems. However, all of these studies assumed predetermined active or standby strategies for each subsystem. In this paper, for the first time, we propose a k-out-of-n system with a choice of redundancy strategies. Therefore, a k-out-of-n series–parallel system is considered when the redundancy strategy can be chosen for each subsystem. In other words, in the proposed model, the redundancy strategy is considered as an additional decision variable and an exact method based on integer programming is used to obtain the optimal solution of the problem. As the optimization of RAP belongs to the NP-hard class of problems, a modified version of genetic algorithm (GA) is also developed. The exact method and the proposed GA are implemented on a well-known test problem and the results demonstrate the efficiency of the new approach compared with the previous studies.

    Keywords: Redundancy allocation problem, Reliability optimization, Choice of redundancy strategies, k, out, ofn system
  • مانی شریفی *، کامران دشتی ملجایی، قاسم چراغ

    در این نوشتار مدل جدیدی برای مسئله ی تخصیص افزونگی با ساختار سری موازی و زیرسیستم های k-o u t-o f-n با در نظر گرفتن «نرخ خرابی وابسته به تعداد اجزای در حال کار» ارائه شده که در آن سیاست افزونگی آماده به کار سرد یا فعال برای زیرسیستم ها در نظر گرفته می شود. هدف، تعیین سیاست افزونگی، نوع و تعداد اجزاء مازاد تخصیص یافته به هر زیرسیستم به منظور بیشینه سازی قابلیت اطمینان و کمینه سازی هزینه ی کل سیستم تحت محدودیت وزن است. به دلیل N P-h a r d بودن مسئله از دو الگوریتم فراابتکاری «الگوریتم ژنتیک مرتب سازی نامغلوب 2» (N S G A I I) و «الگوریتم ژنتیک رتبه بندی نامغلوب»)N R G A(برای حل مدل و از روش سطح پاسخ برای تنظیم پارامترها استفاده شده است. همچنین با استفاده از پنج شاخص عملکردی، عملکرد الگوریتم ها مورد بررسی و مقایسه قرار گرفته است. در انتها نیز برای تحلیل نتایج و اثبات درستی روند استفاده از این الگوریتم ها از آزمون فرض استفاده شده است.

    کلید واژگان: مسئله ی تخصیص افزونگی، زیرسیستم k، o u t، o f، n، نرخ خرابی وابسته به تعداد اجزای در حال کار، سیاست افزونگی، N S G A I I، N R G A
    M. SHARIFI *, K. DASHTI MALJAII, G. CHERAGH

    Nowadays, with technological advances and the need for high reliable systems, extensive research has been done in the eld of reliability optimization. Redundancy allocation problem (RAP) is one of the main issues that has been raised in relation to this subject. Many studies have been carried out in this area and many solutions such as redundancy allocations and component failure rate reduction have been brought up to increase the system reliability. In this paper we considered a seriesparallel system with k-out-of-n subsystems and developed a RAP with components failure rate that depend on the number of working components. In this type of failure rate, when a component fails, the remained components work with more pressure and failure rate of these components increases. The system redundancy strategies are considered as cold standby or active for the subsystems. This model has two objective functions (1) maximizing system reliability and (2) minimizing the system cost. The goals of this model are to select the redundancy strategy between active and cold standby and to determine component type and number of allocated redundant components to each subsystem. As RAP belongs to NP-hard problems, so it is very dicult to optimally solve such a problem by using traditional optimization tools. Therefore for solving the model, two e ective meta-heuristic algorithms named Non-dominated Sorting Genetic Algorithm (NSGAII) and Non-dominated Ranked Genetic Algorithm (NRGA) are presented. We use design of experiment (DOE) for parameter tuning of this algorithms response surface methodology (RSM) is applied for determining the optimum amount of parameters. Then to illustrate the e ectiveness of algorithms, a numerical example is presented and algorithms are compared using ve di erent performance metrics. In order to determine whether there is a signi cant di erence between the performance of algorithms, a single factor ANOVA in signi cant level ( = 0:05) is performed. Finally performance of the algorithms is analyzed and the results are reported.

    Keywords: Redundancy allocation problem, k-out-o-n, redundancy strategies, NSGA II
  • Mani Sharifi, Pedram Pourkarim Guilani, Mohammadreza Shahriari
    in the new production systems, finding a way to improving the product and system reliability in design is a very important. The reliability of the products and systems may improve using different methods. One of this methods is redundancy allocation problem. In this problem by adding redundant component to sub-systems under some constraints, the reliability improved. In this paper we worked on a three objectives redundancy allocation problem. The objectives are maximizing system reliability and minimizing the system cost and weight. The structure of sub-systems are k-out-of-n and the components have constant failure rate. Because this problem belongs to Np. Hard problems, we used NSGA II multi-objective Meta-heuristic algorithm to solving the presented problem.
    Keywords: reliability, Redundancy allocation problem, multi, objectives problem, k, out, of, n, NSGA II algorithm
  • S. J. Sadjadi *, A. Makui, E. Zangeneh, S. E. Mohammadi
    Redundancy allocation is one of the common techniques to increase the reliability of the bridge systems. Many studies on the general redundancy allocation problems assume that the redundancy strategy for each subsystem is predetermined and fixed. In general, active redundancy has received more attention in the past. However, in real world, a particular system design contains both active and cold-standby redundancies, and the choice of the redundancy strategy becomes an additional decision variable. So, the problem is to select redundancy level for each subsystem, component and the best redundancy strategy in order to maximize the system reliability under system-level constraints. This paper presents a new mathematical model for redundancy allocation problem (RAP) for the bridge systems when the redundancy strategy can be selected for individual subsystems. The problem is classified as an NP-hard problem. In this paper, a special version of genetic algorithm (GA) is applied, which has been modified for constrained integer nonlinear problems. Finally, computational results for a typical scenario are presented.
    Keywords: Reliability Optimization, Redundancy Allocation Problem, Complicated Systems, Redundancy Strategies, Genetic Algorithm
  • Mani Sharifi *, Mohsen Yaghoubizadeh
    Considering the increasingly high attention to quality, promoting the reliability of products during designing process has gained significant importance. In this study, we consider one of the current models of the reliability science and propose a non-linear programming model for redundancy allocation in the series-parallel systems according to the redundancy strategy and considering the assumption that the failure rate depends on the number of the active elements. The purpose of this model is to maximize the reliability of the system. Internal connection costs, which are the most common costs in electronic systems, are used in this model in order to reach the real-world conditions. To get the results from this model, we used meta-heuristic algorithms such as genetic algorithm and simulation annealing after optimizing their operators’ rates by using response surface methodology.
    Keywords: Reliability, Redundancy allocation problem, Genetic algorithm, simulated annealing, Response surface methodology
  • P. Pourkarim Guilani, M. Sharifi, S.T.A. Niaki, A. Zaretalab
    The redundancy allocation is one of the most important and useful problems in system optimization, especially in electrical and mechanical systems. The object of this problem is to maximize system reliability or availability within a minimum operation cost. Many works have been proposed in this area so far to draw the problem near to real-world situations. While in classic models the system components are assumed to have two states of working and failed, in this paper, parallel components of serial sub-systems are considered to work in three states, each with a certain performance rate. The component states are classified into two working states of working with full performance and working with half performance, and a failed state. Besides, technical and organizational activities are considered to improve the performance of the components as well as the sub-systems. As the problem belongs to the class of NP-Hard, a genetic algorithm is utilized to solve it.
    Keywords: Reliability, Multi, state systems, Redundancy allocation problem, Three, state components, Genetic algorithm
  • Maghsoud Amiri, Mohammadreza Sadeghi, Ali Khatami Firoozabadi, Fattah Mikaeili
    The main goal in this paper is to propose an optimization model for determining the structure of a series-parallel system. Regarding the previous studies in series-parallel systems, the main contribution of this study is to expand the redundancy allocation parallel to systems that have repairable components. The considered optimization model has two
    Objectives
    maximizing the system mean time to first failure and minimizing the total cost of the system. The main constraints of the model are: maximum number of the components in the system, maximum and minimum number of components in each subsystem and total weight of the system. After establishing the optimization model, a multi objective approach of Imperialist Competitive Algorithm is proposed to solve the model.
    Keywords: redundancy allocation problem, series, parallel system, repairable components, multi objective optimization, imperialist competitive algorithm
  • R. Azizmohammadi, M. Amiri, R. Tavakkoli, Moghaddam, M. Mohammadi
    A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective function. As telecommunications, manufacturing and power systems are becoming more and more complex, while requiring short developments schedules and very high reliability, it is becoming increasingly important to develop efficient solutions to the RAP. In this paper, a new hybrid multi-objective imperialist competition algorithm (HMOICA) based on imperialist competitive algorithm (ICA) and genetic algorithm (GA) is proposed for the first time in multi-objective redundancy allocation problems. In the multi-objective formulation, the system reliability is maximized while the cost and volume of the system are minimized simultaneously. Additionally, a response surface methodology (RSM) is employed to tune the ICA parameters. The proposed HMOICA is validated by some examples with analytical solutions. It shows its superior performance compared to a non-dominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy algorithm (PAES). Finally, the conclusion is given.
    Keywords: Redundancy allocation problem, Response surface methodology, Multi, objective optimization, Imperialist competitive algorithm
  • H. Karimi, A.A. Najafi *
    In this paper, we consider a reliability redundancy optimization problem in a series-parallel type system employing the redundancy strategy of cold-standby. The problem consists of two parts component selection and determination of redundancy level of each component—which need to be solved so that the mean lifetime of the system can be maximized. The redundancy allocation problem is nondeterministic polynomial-time hard and is solved by a combined genetic algorithm - simulation approach. Finally, this algorithm is tested on 33 benchmark problems.
    Keywords: Reliability, Redundancy allocation problem, Monte Carlo Method, Genetic algorithm, means time to failure
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