Multi-objective reliability optimization for dissimilar-unit cold-standby systems using a genetic algorithm

Azaron, Amir; Perkgoz, Cahit; Katagiri, Hideki; Kato, Kosuke; Sakawa, Masatoshi

doi:10.1016/j.cor.2008.02.017

Cited by 52 publications

(29 citation statements)

References 30 publications

(51 reference statements)

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“…It is gratifying therefore that Safari (2012) and Chambari et al (2012) depart from this. Redundancies involving standby components (especially cold standby as in both Safari (2012) and Chambari et al (2012)) have also not received much attention (Azarm et al, 2008). These are interesting drawbacks or gaps, on account of the many practical situations which are likely to depart from such fundamentals.…”

Section: Discussionmentioning

confidence: 99%

Models in design for reliability optimisation

Twum¹,

Aspinwall

2013

AJSIR

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This paper presents a state of the art review of the vibrant and fast growing field of reliability optimisation in design as it was in the early 1980s, when the field had started to gain attention, to date; in terms of research and development of theories and applications. The field is classified into the pertinent existing reliability optimisation strategies and the types of optimisation models employed. The solution methods used are also discussed. The models are critically reviewed and gaps needing attention noted. Particularly noted was the dominance of redundancy allocation optimisation over other strategies such as reliability allocation optimisation which virtues have not been fully explored. Attention is drawn also to the scarcity of multi-objective optimisation models in the literature, even though typically real life reliability optimisation problems are of that nature. The discussions are concluded by drawing attention to potential model formulations of the multiobjective type.

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Section: Discussionmentioning

confidence: 99%

Models in design for reliability optimisation

Twum¹,

Aspinwall

2013

AJSIR

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“…The same objective functions as those defined in Kumar et al (2006) were used. Azaron et al (2009) found Pareto solutions in a cold-standby redundancy scheme using genetic algorithms and the goal attainment method in order to minimize the initial purchase cost of the system, to maximize its MTTF (mean time to failure), to minimize its VTTF (variance of time to failure) and also to maximize its reliability during the mission time. studied the optimal expansion of an existing electrical power transmission network using multiobjective genetic algorithms with two objectives: maximizing reliability and minimizing cost.…”

Section: Approaches In the 2000s And 2010smentioning

confidence: 99%

Other Risk, Reliability and Maintenance Decision Problems

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Abstract:In this chapter, specific problems in risk, reliability and maintenance context are described, such as location of backup units, sequencing of maintenance activities, natural disasters, operation planning of a power system network, integrated production and maintenance scheduling, maintenance team sizing and reliability acceptance tests. This chapter presents a multicriteria decision model with an illustrative application for most of these problems. Amongst the MCDM/A approaches considered for the illustrative applications in this chapter are: Multiattribute utility theory (MAUT), PROMETHEE II, NSGA-II. Regarding the reliability acceptance test an MCDM/A Bayesian approach is presented. For these problems, several aspects have been considered such as: size of population, degree of industrialization, the extent of health services (location of backup units); degree of damage, consumption, electric load, special clients, healthcare services, SAIDI and SAIFI (sequencing of maintenance activities); human, environmental, financial and infrastructure concerns (natural disasters); expected tardiness and maintenance costs (integrated production and maintenance scheduling); waiting time and cost of personnel (maintenance team sizing); probability of accepting equipment not in accordance with the reliability specified by the manufacturer; and delaying the project conclusion (reliability acceptance test). Finally, some aspects of multiobjective optimization are discussed.

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“…Performance (84) ADL(4) [145], [160], [161], [170], ANY(2) [133], [153], CUSTOMAM(5) [90], [152], [196]- [198], OPTIMPL(3) ALLOCATION(20) [61], [83], [88], [121]- [123], [133], [153], [155], [160], [161], [164], [175]- [178], [186], [187], [192], [214], CLUSTERING(3) [67], [122], [214], COMPONENT SELECTION(12) [7], [18], [96], [97], [147], [149], [160], [161], [177], [178], [182], [232], HARDWARE PARAMETERS(2) [160], [161], HARDWARE REPLICATION(29) [31], [51]- [57], …”

Section: Qa Architecture Representation Quality Evaluation Degrees Ofmentioning

confidence: 99%

“…Evolutionary Algorithms (EAs) [18], [33], [37], [38], [41], [57]- [60], [71], [73], [76], [88], [92], [102], [108], [118], [128], [148], [149], [157]- [159], [161], [175], [196], [216], [221], [223], [227]- [229], [231], [237] are some of the most commonly used approximate methods in architecture optimization. EAs are seen as robust algorithms that exhibit approximately similar performance over a wide range of problems [98], hence their popularity in the software engineering domain.…”

Section: Qa Optimization Strategy Type Constraint Handlingmentioning

confidence: 99%

Software Architecture Optimization Methods: A Systematic Literature Review

Aleti

Bühnová

Grunske

et al. 2013

IIEEE Trans. Software Eng.

243

146

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Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Abstract-Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.

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Multi-objective reliability optimization for dissimilar-unit cold-standby systems using a genetic algorithm

Cited by 52 publications

References 30 publications

Models in design for reliability optimisation

Models in design for reliability optimisation

Other Risk, Reliability and Maintenance Decision Problems

Software Architecture Optimization Methods: A Systematic Literature Review

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