Reliability optimization and redundancy allocation for fire extinguisher drone using hybrid PSO–GWO

Bhandari, Ashok Singh; Kumar, Akshay; Ram, Mangey

doi:10.1007/s00500-023-08560-8

Cited by 7 publications

(4 citation statements)

References 53 publications

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“…Following a parallel argumentation with the one implemented at part (i), we next substitute Formulas ( 12), ( 16) and ( 17) in (18) and the expression we are chasing for is concluded after some straightforward manipulations.…”

Section: (I)mentioning

confidence: 99%

“…(ii) The MTTF (E(T NET )) of the parallel network NET(ξ,m,k,n) can be determined via (20). Following a parallel argumentation with (i) partially implemented, we next substitute Formulas (12), ( 17) and ( 21) in (18) and the expression we are searching for is concluded after some straightforward manipulations.…”

Section: (I)mentioning

confidence: 99%

“…Moreover, the dilemma of whether the cold standby redundancy is more effective when it is applied at system level or at component level has attracted the attention of some researchers (see, e.g., [13][14][15][16]). For additional surveys concerning the cost optimization or optimal allocation in reliability structures, the interested reader is referred to [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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An Archimedean Copulas-Based Approach for m-Consecutive-k-Out-of-n: F Systems with Exchangeable Components

Triantafyllou

2023

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It is evident that several real-life applications, such as telecommunication systems, call for the establishment of consecutive-type networks. Moreover, some of them require more complex connectors than the ones that exist already in the literature. Thereof, in the present work we provide a signature-based study of a reliability network consisting of identical m-consecutive-k-out-of-n: F structures with exchangeable components. The dependency of the components of each system is modeled with the aid of well-known Archimedean copulas. Exact formulae for determining the expected lifetime of the underlying reliability scheme are provided under different Archimedean copulas-based assumptions. Several numerical results are carried out to shed light on the performance of the resulting consecutive-type design. Some thoughts on extending the present study to more complex consecutive-type reliability structures are also discussed.

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Section: (I)mentioning

confidence: 99%

Section: (I)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Archimedean Copulas-Based Approach for m-Consecutive-k-Out-of-n: F Systems with Exchangeable Components

Triantafyllou

2023

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“…A hybrid version called hPSO-GSA was proposed from the combination of PSO and GSA for feature selection [77]. A hybrid version made from PSO and GWO called hPSO-GWO was developed to deal with reliability optimization and redundancy allocation for fire extinguisher drones [78]. A hybrid PSO-GA approach was proposed for flexible flow shop scheduling with transportation [79].…”

Section: Literature Reviewmentioning

confidence: 99%

A New Hybrid Particle Swarm Optimization–Teaching–Learning-Based Optimization for Solving Optimization Problems

Hubálovský,

Hubálovská,

Matoušová

2023

Biomimetics

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This research paper develops a novel hybrid approach, called hybrid particle swarm optimization–teaching–learning-based optimization (hPSO-TLBO), by combining two metaheuristic algorithms to solve optimization problems. The main idea in hPSO-TLBO design is to integrate the exploitation ability of PSO with the exploration ability of TLBO. The meaning of “exploitation capabilities of PSO” is the ability of PSO to manage local search with the aim of obtaining possible better solutions near the obtained solutions and promising areas of the problem-solving space. Also, “exploration abilities of TLBO” means the ability of TLBO to manage the global search with the aim of preventing the algorithm from getting stuck in inappropriate local optima. hPSO-TLBO design methodology is such that in the first step, the teacher phase in TLBO is combined with the speed equation in PSO. Then, in the second step, the learning phase of TLBO is improved based on each student learning from a selected better student that has a better value for the objective function against the corresponding student. The algorithm is presented in detail, accompanied by a comprehensive mathematical model. A group of benchmarks is used to evaluate the effectiveness of hPSO-TLBO, covering various types such as unimodal, high-dimensional multimodal, and fixed-dimensional multimodal. In addition, CEC 2017 benchmark problems are also utilized for evaluation purposes. The optimization results clearly demonstrate that hPSO-TLBO performs remarkably well in addressing the benchmark functions. It exhibits a remarkable ability to explore and exploit the search space while maintaining a balanced approach throughout the optimization process. Furthermore, a comparative analysis is conducted to evaluate the performance of hPSO-TLBO against twelve widely recognized metaheuristic algorithms. The evaluation of the experimental findings illustrates that hPSO-TLBO consistently outperforms the competing algorithms across various benchmark functions, showcasing its superior performance. The successful deployment of hPSO-TLBO in addressing four engineering challenges highlights its effectiveness in tackling real-world applications.

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Enhancing cast iron industry efficiency through stochastic Petri nets simulation modeling of cylinder block systems

Urvashi,

Bansal

2024

Int J Interact Des Manuf

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Reliability optimization and redundancy allocation for fire extinguisher drone using hybrid PSO–GWO

Cited by 7 publications

References 53 publications

An Archimedean Copulas-Based Approach for m-Consecutive-k-Out-of-n: F Systems with Exchangeable Components

An Archimedean Copulas-Based Approach for m-Consecutive-k-Out-of-n: F Systems with Exchangeable Components

A New Hybrid Particle Swarm Optimization–Teaching–Learning-Based Optimization for Solving Optimization Problems

Enhancing cast iron industry efficiency through stochastic Petri nets simulation modeling of cylinder block systems

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