Synchronization and control of chaos in supply chain management

Göksu, Alper; Kocamaz, Uğur Erkin; Uyaroğlu, Yılmaz

doi:10.1016/j.cie.2014.09.025

Cited by 64 publications

(30 citation statements)

References 28 publications

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“…By using ontologies, such as semantic Web technologies (Munoz et al 2015), organizations are rede- (Soliman et al 2005, Ryoo and Kim 2015, Göksu et al 2015, knowledge redundancy (Sivakumar and Roy 2004), knowledge exploitation (Soliman et al 2005), knowledge discovery ), and planning. With these organizational changes, flexible and scalable information technologies are preferred in order to take advantage of the know-how from supply chains.…”

Section: Supply Chain and Knowledge Managementmentioning

confidence: 99%

Supply chain knowledge management supported by a simple knowledge organization system

Rodríguez-Enríquez

Alor-Hernández

Mejia-Miranda

et al. 2016

Electronic Commerce Research and Applications

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Section: Supply Chain and Knowledge Managementmentioning

confidence: 99%

Supply chain knowledge management supported by a simple knowledge organization system

Rodríguez-Enríquez

Alor-Hernández

Mejia-Miranda

et al. 2016

Electronic Commerce Research and Applications

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“…There has not been any article for chaos control in the supply chain, and only the optimal management of effective factors has been studied. The only research in this area deals with the synchronization of two identical chaotic supply chain management systems based on their mathematical model (Goksu et al, 2015). Similar systems have been studied relatively well.…”

Section: Introductionmentioning

confidence: 99%

Robust controlling of chaotic behavior in supply chain networks

Nav

Motlagh

Makui

2017

Journal of the Operational Research Society

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The supply chain network is a complex nonlinear system that may have a chaotic behavior. This network involves multiple entities that cooperate to meet customers demand and control network inventory. Although there is a large body of research on measurement of chaos in the supply chain, no proper method has been proposed to control its chaotic behavior. Moreover, the dynamic equations used in the supply chain ignore many factors that affect this chaotic behavior. This paper offers a more comprehensive modeling, analysis, and control of chaotic behavior in the supply chain. A supply chain network with a centralized decision-making structure is modeled. This model has a control center that determines the order of entities and controls their inventories based on customer demand. There is a time-varying delay in the supply chain network, which is equal to the maximum delay between entities. Robust control method with linear matrix inequality technique is used to control the chaotic behavior. Using this technique, decision parameters are determined in such a way as to stabilize network behavior.

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“…Since the pioneer study of Ott et al in 1990 [29], several effective methods for the control of chaotic systems have been proposed. The chaos control approaches include linear feedback control [13,15,16,18,22,24,41,44,47], nonlinear feedback control [7], time-delayed feedback control [34], adaptive control [2,40], sliding mode control [22,12], passive control [8,22,28,33,45], backstepping design [12,32], and intelligent control [20] methods. Among them, the linear feedback control has been widely used due to its simplicity of implementation.…”

Section: Introductionmentioning

confidence: 99%

“…It stabilizes the chaotic system with the negative feedback gains of related state variables. In recent years, it has been applied for the control of Lorenz [47], Chua [18], Rössler [16], Chen [13], Lü [24], Liu [41], four-dimensional Rabinovich [22], and many other chaotic systems [15,44]. If another feedback state variable gain is used, then it is named as dislocated feedback control method.…”

Section: Introductionmentioning

confidence: 99%

Controlling Hyperchaotic Finance System with Combining Passive and Feedback Controllers

Kocamaz

Göksu

Uyaroğlu

et al. 2018

ITC

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In this paper, a novel control method that combines passive, linear feedback, and dislocated feedback control methods is proposed and applied to the control of the four-dimensional hyperchaotic finance system which has been introduced and controlled with the linear feedback and speed feedback control methods by Yu, Cai, and Li (2012). The stability of the hyperchaotic finance system at its equilibrium points is ensured on the basis of a Lyapunov function. Computer simulations are used for verifying all the theoretical analyses visually. In the simulations, the proposed control method is also compared with the speed feedback and linear feedback control methods to observe its effectiveness. Finally, the comparative findings are discussed.

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Synchronization and control of chaos in supply chain management

Cited by 64 publications

References 28 publications

Supply chain knowledge management supported by a simple knowledge organization system

Supply chain knowledge management supported by a simple knowledge organization system

Robust controlling of chaotic behavior in supply chain networks

Controlling Hyperchaotic Finance System with Combining Passive and Feedback Controllers

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