Optimization by Integer Programming of Constrained Reliability Problems with Several Modes of Failure

Tillman, Frank A.

doi:10.1109/tr.1969.5216977

Cited by 43 publications

(5 citation statements)

References 8 publications

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“…A variety of algorithms, as summarized in Tillman et al (1977), and more recently by Kuo & Prasad (2000), Kuo & Wan (2007), including exact methods, heuristics and meta-heuristics have already been proposed for the RRAP. An exact optimal solution is obtained by exact methods such as cutting plane method (Tillman, 1969), branch-and-bound algorithm (Chern & Jan, 1986;Ghare & Taylor, 1969), dynamic programming (Bellman & Dreyfus, 1958;Fyffe et al, 1968;Nakagawa & Miyazaki, 1981;Yalaoui et al, 2005), and goal programming (Gen et al, 1989). However, as the size of problem gets larger, such methods are difficult to apply to get a solution and require more computational effort.…”

Section: The Reliability-redundancy Allocation Problem (Rrap)mentioning

confidence: 99%

Real-World Applications of Genetic Algorithms

Roeva¹

2012

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Dr. Olympia Roeva received the M.Sc. degree (1998) and Ph.D. degree (2007) from the Technical University -Sofia, Bulgaria. At present she is an associate professor in Department of Bioinformatics and Mathematical Modeling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences. Dr. Roeva is one of the scientists playing a significant role in the renovation of International Journal Bioautomation. She has received various scientific awards, including a Diploma from Union of Scientists in Bulgaria for High Scientific Achievements 2008. Her research interests are in the fields of modeling, optimization and control of cultivation processes, functional state modeling approach, metaheuristic algorithms and generalized nets.

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Section: The Reliability-redundancy Allocation Problem (Rrap)mentioning

confidence: 99%

Real-World Applications of Genetic Algorithms

Roeva¹

2012

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“…A separable function can be analyzed as a multistage process to which the methods of dynamic programming (Bellman and Dreyfus, 1958;Fyffe et al, 1968;Kettelle, 1962;Liittschwager, 1964;Messinger and Shooman, 1970;Misra, 1971b;Woodhouse, 1962) and discrete maximum principle (Fan et al, 1967;Tillman et al, 1968) are applicable. The problem may also be transformed and solved as an integer programming problem (Ghare and Taylor, 1969;Misra, 1971a;Mizukami, 1968;Tillman and Liittschwager, 1967;Tillman, 1969) or by using the Lagrangian multipliers technique (Barlow et al, 1965;Banerjee and Rajamani, 1973;Everett, 1963;Messinger and Shooman, 1970;Misra, 1972). The concept of dominating sequence (or a family of uncominated allocations) has also been used to solve the problem (Barlow et al, 1965;Black and Proschan, 1959;Kettelle, 1962;Messinger and Shooman, 1970;Proschan and Bray, 1965).…”

Section: Availability Of Complex Systemsmentioning

confidence: 99%

Process reliability analysis

Henley

Gandhi

1975

AIChE Journal

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This paper presents a unified approach for obtaining system reliability and availability parameters from block diagram representations of process systems. It starts with computer algorithms for obtaining the minimal paths in a system, then shows how this information can be combined with unit reliability data to obtain the overall system reliability, and the response of system reliability to changes in unit reliability (sensitivities). It then demonstrates how these sensitivities can be used to optimize the system reliability and availability by equipment redundancy. Extension of the methodology to the automated production of system fault trees as well as the mathematical relationship between fault trees and block diagrams are noted. ERNEST SCOPEThe trend to larger, more complex, and highly interdependent process systems has been in evidence for some time. With increasing scale, repair becomes more costly in both time and money, startup and shutdown losses increase, and the vulnerability of the plant becomes a matter of grave concern. Further factors spurring the process industries' interest in reliability analysis are the high cost of maintenance, which now is as much as 10% of plant cost/annum, and the problems associated with insurance, siting, environmental degradation due to failures, and the establishment of a good public image.In this paper we focus attention on analytical methods whereby system reliability parameters can be obtained from block-diagrammatic representation of process flow sheets. Although other techniques, such as state enumeration methods are treated, primary emphasis is on the development of path enumeration methods by which the reliability parameters of complex (nonseries-parallel) systems can be computed. As demonstrated in the paper, this approach is particularly powerful because it also permits calculation of the sensitivity of the overall system reliability to changes in configuration and unit reliability. These sensitivities, being gradients, are then used in conjunction with integer, gradient-based, optimization algorithms to solve problems involving allocation of equipment and maintenance intervals.Also discussed are the construction of fault trees and some potentially useful algorithms for their automated construction from block diagrams. CONCLUSION AND SIGNIFICANCEThe increasing interest of the chemical industry in reliability analysis is clearly demonstrated by the fact that only three articles on this subject appeared in the chemical engineering literature prior to 1971, and more than 16 have been published since. To date, the process industry has depended almost completely on computational methods developed by the military, electronic, aerospace, and nuclear industries where primary concern is catastrophic failure of essentially nonrepairable systems.In attempting to apply previously developed methods to process systems, one finds that they do not readily lend themselves to many of the problems of interest to chemical engineers who generally must deal with multicomponent stre...

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“…In 1968 the detailed method to handle RAP was presented, which was planned for the decision of the ideal course of action. 3 After this, some researchers proposed various techniques to address RAP in which the exact methods were carried out at first which were long processing methods [4][5][6][7] and later on heuristic strategies like GA, PSO, hybrid GA-PSO, hybrid PSO, Cuckoo Search, GWO and so on taken into consideration [8][9][10][11][12][13] . These heuristic strategies were giving approximated outcomes in very little time when contrasted with exact methods.…”

Section: Introductionmentioning

confidence: 99%

Grey wolf optimizer and hybrid PSO‐GWO for reliability optimization and redundancy allocation problem

Bhandari

Kumar

Ram

2023

Quality & Reliability Eng

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Analysis and optimization of system reliability have very much importance for developing an optimal design for the system while using the available resources. Several studies are centered towards reliability optimization using metaheuristics. In this study, a recently developed metaheuristic optimization algorithm called hybrid PSO-GWO (HPSGWO) to solve the reliability-redundancy optimization problem has been proposed. The HPSGWO fuses the Particle Swarm Optimization's (PSO) exploitation ability with the grey wolf optimizer's (GWO) exploration ability. The comparison of results with prior best results of PSO and GWO for the four benchmarks of reliability redundancy allocation problem demonstrates the HPSGWO as a productive enhancement strategy since it got promising answers than other metaheuristic algorithms.

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Optimization by Integer Programming of Constrained Reliability Problems with Several Modes of Failure

Cited by 43 publications

References 8 publications

Real-World Applications of Genetic Algorithms

Real-World Applications of Genetic Algorithms

Process reliability analysis

Grey wolf optimizer and hybrid PSO‐GWO for reliability optimization and redundancy allocation problem

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