Robust exponential stability criteria of uncertain stochastic systems with time-varying delays

Li, Yumei; Guan, Xinping; Luo, Xiaoyuan

doi:10.1080/00207720802645212

Cited by 11 publications

(3 citation statements)

References 17 publications

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“…The solution s is robust (Li, Guan, and Luo 2011) in the sense that its value does not deviate abruptly as a result of the stochastic behaviours of customer demands in VRPSD. If a solution obtained for VRPSD is highly sensitive to small perturbation in customer demands, its performance becomes unreliable for use in VRPSD (Tsutsui and Ghosh 1997).…”

Section: Vehicle Routing Problem With Stochastic Demandsmentioning

confidence: 98%

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

Chen

Feng

Ong

2012

International Journal of Systems Science

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In this article, we proposed a self-adaptive memeplex robust search (SAMRS) for finding robust and reliable solutions that are less sensitive to stochastic behaviours of customer demands and have low probability of route failures, respectively, in vehicle routing problem with stochastic demands (VRPSD). In particular, the contribution of this article is three-fold. First, the proposed SAMRS employs the robust solution search scheme (RS 3 ) as an approximation of the computationally intensive Monte Carlo simulation, thus reducing the computation cost of fitness evaluation in VRPSD, while directing the search towards robust and reliable solutions. Furthermore, a self-adaptive individual learning based on the conceptual modelling of memeplex is introduced in the SAMRS. Finally, SAMRS incorporates a gene-meme co-evolution model with genetic and memetic representation to effectively manage the search for solutions in VRPSD. Extensive experimental results are then presented for benchmark problems to demonstrate that the proposed SAMRS serves as an efficable means of generating high-quality robust and reliable solutions in VRPSD.

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Section: Vehicle Routing Problem With Stochastic Demandsmentioning

confidence: 98%

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

Chen

Feng

Ong

2012

International Journal of Systems Science

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“…[8] extended the integral inequality method to the nonlinear stochastic uncertain delay systems, and obtained a delay-dependent stability criteria. [9] studied the robust exponential stability of a kind of neutral stochastic Markov jump systems, and gave the sufficient conditions of robust exponential stability for the systems. [10] studied the stability of a kind of neutral stochastic neural networks with Markov jump by using the segmentation method.…”

Section: Robust Control and Stability Analysis Of Stochastic Systemsmentioning

confidence: 99%

Robust Analysis and Control of Stochastic Interval Systems

Wang¹,

Rao²

2015

Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering

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Abstract. Stochastic interval systems is a new type of stochastic system in recent years, which is a new field integrated by information and control. This paper introduces the research history and the newest research trends of stochastic interval systems, and presents many widespread theoretical and application problems. Moreover, some new research topics and directions related to stochastic interval systems are proposed. IntroductionFor many problems in natural world, socio-economic, material systems of practical engineering, their dynamic rules can be described by deterministic dynamic model or random system model. The description of deterministic system model is by deterministic ordinary differential equations, which is to simplify the process of the actual system. Its system model is relatively simple, and is easy to analyze and synthesize, and its research tool is also relatively simple. When the considered system is under ideal conditions or system accuracy is not required, the system is often reduced to a deterministic model.Since the creation of modern control theory, control theory based on deterministic system model has been developing rapidly, and played an important role in practical applications. However, in many practical systems, such as engineering controls, traffic management, physical circuit system, the random factor is objective and inevitable. Due to the perturbations by the internal structure parameter, the system control inputs and the external environment, the established model can not accurately describe the controlled object or the system creates deviation between the running model and the actual object. In large-scale integrated circuits, interference of random factors is inevitable. To ignore the interference of random factors will increase the systematic errors and affect system performance. On the radio circuit receiving system, due to the random noise disturbance outside, the received signal of a radio is unstable. Thus, random factors are worth considering.With the development of science and technology, the system accuracy requirements of practical engineering technology become more and more high. The original simplified deterministic model can not meet the accuracy requirements of the system. The system designed by deterministic model in operation will deviate from predetermined design requirements, resulting in the generation of random deviation. Therefore, in the system modeling, we should fully consider the impact of random factors on the system, and use a stochastic model for system modeling and use the stochastic point of view for the system analysis and synthesis. Stochastic system model is described by stochastic ordinary differential equations. In a sense, the theory of stochastic systems are the combination product of deterministic systems theory and stochastic processes.In most actual operation of the control system, there are more or less uncertain factors, such as the measurement error of physical components, the impact of limited word length of memory, and outside in...

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“…RP SD (τ k ) is the expected distance traveled by vehicle v k . The solution s is robust[112] in the sense that its value does not deviate abruptly as a result of the stochastic…”

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confidence: 99%

A study on memetic computation, with applications to capacitated vehicle routing problems

Chen¹

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Memetic computation, a paradigm that uses the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving, represents one of the frontiers in the computational intelligence research, of today's optimization research. This dissertation takes an explorative attitude in the design of memetic computing frameworks and algorithms by leveraging the co-adaptive nature of meme complexes or memeplexes. The current research presented in this dissertation takes multi-memes and memeplexes as focal point of interest in the context of memetic computation and develop meme-centric computing frameworks for more effective problem-solving in the context of stochastic optimization of Capacitated Vehicle Routing Problems (CVRP) and Vehicle Routing Problem with Stochastic Demands (VRPSD). His sincere encouragement during my indecisive moments and inspirational insights into the many aspects of my research direction have faithfully guided me throughout my research work. Without Associate Professor Ong's guidance, the fruitful achievements of this project would not have been possible. I would also like to thank Associate Professor Lim Meng Hiot for his beneficial comments and support. In addition, I would like to thank my friends for their encouragements and the staffs in Intelligent Systems Centre (IntelliSys) and Center for Computational Intelligence for their technical supports. Last but not least, special thanks to my parents for their constant support, understanding and love.

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Robust exponential stability criteria of uncertain stochastic systems with time-varying delays

Cited by 11 publications

References 17 publications

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

A self-adaptive memeplexes robust search scheme for solving stochastic demands vehicle routing problem

Robust Analysis and Control of Stochastic Interval Systems

A study on memetic computation, with applications to capacitated vehicle routing problems

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