Reliability optimization of topology communication network design using an improved ant colony optimization

Watcharasitthiwat, Kanyapat; Wardkein, P.

doi:10.1016/j.compeleceng.2009.02.006

Cited by 44 publications

(19 citation statements)

References 17 publications

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“…FS process was performed using genetic algorithm (GA), particle swarm optimization (PSO), ACO and IACO algorithms. In order to overcome general drawbacks of ACO such as early stagnation [31] and low convergence speed [32,34,84], the heuristic parameters were adjusted for IACO during the optimization process. Initial feature set is composed of 12 intrahemispheric and 4 inter-hemispheric QEEG coherence values from alpha, delta and theta frequency bands.…”

Section: Resultsmentioning

confidence: 99%

“…The probability to get trapped in local optimal solution, high computational time and system resources requirement to obtain the optimal solution and the difficulties to set the heuristic parameters to achieve the good performance are prominent considerations of the algorithm. So, in order to avoid the potential weaknesses, similar improved ACO methods were proposed in recent studies [31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A wrapper-based approach for feature selection and classification of major depressive disorder–bipolar disorders

Ergüzel

Taş

Çebi

2015

Computers in Biology and Medicine

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A wrapper-based approach for feature selection and classification of major depressive disorder–bipolar disorders

Ergüzel

Taş

Çebi

2015

Computers in Biology and Medicine

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“…Network reliability optimization is widely studied for all kinds of applications, such as power communication network (Watcharasitthiwat and Wardkein 2009), telecommunications (Carlier et al 1997) and so on. Nodes and links in a particular network are selected to achieve certain system reliability, and such analysis process is named as network topological optimization (Abd-El- Barr 2009).…”

Section: Reliability Analysis Of Systems With Network Structuresmentioning

confidence: 99%

Reliability evaluation and component importance measure for manufacturing systems based on failure losses

Zhang

et al. 2015

J Intell Manuf

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Little work has been done to assess the reliability of a vital system like the manufacturing system. In this article, a novel and effective system reliability evaluation method in terms of failure losses has been proposed for manufacturing systems of job shop type, and then the failure losses based component importance measure (CIM) is used for importance analysis of equipment. The former indicates the present system reliability situation and the latter points the way to reliability improvement efforts. In this scheme, the problem is described and modeled by a dynamic directed network. Consider that the actual processing time of machines is to contribute to failure occurrence, it is used to calculate the failure times and failure losses. The obtained total failure times and failure losses of the system are applied to evaluate its reliability. Techniques to estimate two kinds of failure losses based CIMs are presented. They offer guidelines to realize system reliability growth cost-effectively. A case study of a real job shop is provided as an example to demonstrate the validity of the proposed methods. Comparison to other commonly used methods shows the efficiency of the proposed methods. CNCComputer numerical control DNC Distributed numerical control ERP Enterprise resource planning FT Failure times MES Manufacturing execution system MPT Machine processing time MTBF Mean time between failure MTTF Mean time to failure MTTR Mean time to repair OEE Overall equipment effectiveness RFID Radio frequency identification WDN Weighted and directed network WIP Work-in-process t, T Sequence number of time intervals (number of all intervals is T ) i, I t Sequence number of products items (number of all items is I t ) j, J t Sequence number of processes during t (J t is the maximum value) k, K Sequence number of equipment (number of all equipment is K ) G t WDN during t M k Equipment k r k Failure rate of M k F T tk Failure times of M k during t T total Total time V ti Volume size of item i during t B ti j Processing time of item i for the jth process during t x ti jk Be equal to 1 if M k is used for machining the jth process of item i during t, 0 otherwise MT B F k MTBF of M k MT T R k MTTR of M k C k Average maintenance cost for every repair process of M k 123 J Intell Manuf P L tk Production losses for M k during time period t C f k

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“…The goal was to minimize the network design cost under a known constraint on the allterminal reliability. Watcharasitthiwat and Wardkein (2009) used an improved ant colony optimization method to allocate the network mission reliability, and the minimum cost was obtained under the constraints of both two-terminal reliability and all-terminal reliability goals. These methods deal with optimal reliability allocation problems, where the system cost, weight, etc.…”

Section: Introductionmentioning

confidence: 99%

A new method for reliability allocation of avionics connected via an airborne network

Wang

Liao

et al. 2015

Journal of Network and Computer Applications

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Reliability optimization of topology communication network design using an improved ant colony optimization

Cited by 44 publications

References 17 publications

A wrapper-based approach for feature selection and classification of major depressive disorder–bipolar disorders

A wrapper-based approach for feature selection and classification of major depressive disorder–bipolar disorders

Reliability evaluation and component importance measure for manufacturing systems based on failure losses

A new method for reliability allocation of avionics connected via an airborne network

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