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Ding Zhang - One of the best experts on this subject based on the ideXlab platform.
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Modelling inter-supply chain competition with resource limitation and demand disruption
International Journal of Systems Science, 2014Co-Authors: Zhaobo Chen, Chunxian Teng, Ding ZhangAbstract:This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for Illustrative Purpose.
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Supply chain competition model with customer preference: A theoretical perspective
2011 International Conference on Business Management and Electronic Information, 2011Co-Authors: Guo Jie, Ding ZhangAbstract:This paper proposes a mathematical model for supply chain versus supply chain competition with customer preference. The model is based on stochastic user equilibrium and spatial price equilbirum theory with customer choice preference given by Logit model. We present a numerical example for Illustrative Purpose and provide conclusion remarks.
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a network economic model for supply chain versus supply chain competition
Omega-international Journal of Management Science, 2006Co-Authors: Ding ZhangAbstract:We study a supply chain economy (SCE) that comprises heterogeneous SC involving multiple products and competing for multiple markets. The proposed network model is built upon operation links and interface links, representing, respectively, substantial SC operations and coordination functions between the operations. The paper presents a variational inequality formulation of the problem, the solution of which determines the winning SC and their market shares in the equilibrium of SCE. We furnish qualitative properties such as existence and uniqueness of the equilibrium. Numerical examples are presented for Illustrative Purpose.
Bin Liu - One of the best experts on this subject based on the ideXlab platform.
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reliability estimation of stress strength model using finite mixture distributions under progressively interval censoring
Journal of Computational and Applied Mathematics, 2019Co-Authors: Xuchao Bai, Yimin Shi, Yiming Liu, Bin LiuAbstract:Abstract This paper considers the reliability estimation of the stress–strength model based on progressively Type-I interval censored data, where the random stress variable follows a Lindley distribution and the random strength variable follows a finite mixture of exponential distributions. The maximum likelihood estimation and 95% confidence interval estimation of the stress–strength reliability are deduced by using EM algorithm and Bootstrap sampling, respectively. The Bayesian estimation and 95% highest posterior density credible interval of the stress–strength reliability under squared error loss function are obtained by using the Metropolis–Hastings within Gibbs algorithm. To test the homogeneity of the finite mixture distributions, the D-test statistic is introduced. Then, we use the D-test statistic to test the homogeneity of a real data, compare the finite mixture exponential distributions with a single exponential distribution by using the Akaike information criterion (AIC) values, and analyze this data using the proposed methodology. Finally, Monte Carlo simulations are performed for Illustrative Purpose.
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reliability inference of stress strength model for the truncated proportional hazard rate distribution under progressively type ii censored samples
Applied Mathematical Modelling, 2019Co-Authors: Xuchao Bai, Yimin Shi, Yiming Liu, Bin LiuAbstract:Abstract This paper considers the reliability inference for the truncated proportional hazard rate stress–strength model based on progressively Type-II censoring scheme. When the stress and strength variables follow the truncated proportional hazard rate distributions, the maximum likelihood estimation and the pivotal quantity estimation of stress–strength reliability are derived. Based on the percentile bootstrap sampling technique, the 95% confidence interval of stress–strength reliability is obtained, as well as the related coverage percentage. Moreover, based on the Fisher Z transformation and the modified generalized pivotal quantity, the 95% modified generalized confidence interval for the stress–strength reliability is obtained. The performance of the proposed method is evaluated by the Monte Carlo simulation. The numerical results show that the pivotal quantity estimators performs better than the maximum likelihood estimators. At last, two real datasets are analyzed by the proposed methodology for Illustrative Purpose. The results of real example analysis show that our model can be applied to the practical problem, the truncated proportional hazard rate distribution can fit the failure data better than other distributions, and the algorithms in this paper are suitable to handle the small sample data.
Debasis Kundu - One of the best experts on this subject based on the ideXlab platform.
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analysis of weibull step stress model in presence of competing risk
IEEE Transactions on Reliability, 2019Co-Authors: Debashis Samanta, Arindam Gupta, Debasis KunduAbstract:In this paper, we mainly consider the inference of a simple step-stress model based on a complete sample, when the stress changes after a prefixed number of failures. It is assumed that there is more than one cause of failure, and the lifetime of the experimental units at each stress level follows Weibull distribution with the same shape parameter and different scale parameters. The distribution function under different stress levels are connected through the generalized Khamis–Higgins model. The maximum likelihood estimates of the model parameters and the associated asymptotic confidence intervals are obtained. Further, we consider the Bayesian inference of the unknown model parameters based on fairly general prior distributions. We have also provided the results for Type-I censored data also. We assess the performances of the estimators through extensive simulation study for complete sample, and the analyses of one complete (simulated) data set and one Type-I censored solar lighting device data set have been performed for Illustrative Purpose. We propose different classical and Bayesian optimal criteria, and based on them we obtain the optimum stress changing time. Finally, we have indicated how the assumption on the common shape parameter of two competing causes can be relaxed.
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On generalized progressive hybrid censoring in presence of competing risks
Metrika, 2017Co-Authors: Arnab Koley, Debasis KunduAbstract:The progressive Type-II hybrid censoring scheme introduced by Kundu and Joarder (Comput Stat Data Anal 50:2509–2528, 2006 ), has received some attention in the last few years. One major drawback of this censoring scheme is that very few observations (even no observation at all) may be observed at the end of the experiment. To overcome this problem, Cho et al. (Stat Methodol 23:18–34, 2015 ) recently introduced generalized progressive censoring which ensures to get a pre specified number of failures. In this paper we analyze generalized progressive censored data in presence of competing risks. For brevity we have considered only two competing causes of failures, and it is assumed that the lifetime of the competing causes follow one parameter exponential distributions with different scale parameters. We obtain the maximum likelihood estimators of the unknown parameters and also provide their exact distributions. Based on the exact distributions of the maximum likelihood estimators exact confidence intervals can be obtained. Asymptotic and bootstrap confidence intervals are also provided for comparison Purposes. We further consider the Bayesian analysis of the unknown parameters under a very flexible beta–gamma prior. We provide the Bayes estimates and the associated credible intervals of the unknown parameters based on the above priors. We present extensive simulation results to see the effectiveness of the proposed method and finally one real data set is analyzed for Illustrative Purpose.
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on estimation of r p y x for exponential distribution under progressive type ii censoring
Journal of Statistical Computation and Simulation, 2012Co-Authors: Bugra Saracoglu, Ismail Kinaci, Debasis KunduAbstract:This paper deals with the estimation of the stress–strength parameter R=P(Y
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Estimating the parameters of the Marshall-Olkin bivariate Weibull distribution by EM algorithm
Computational Statistics & Data Analysis, 2009Co-Authors: Debasis Kundu, Arabin Kumar DeyAbstract:In this paper we consider the Marshall-Olkin bivariate Weibull distribution. The Marshall-Olkin bivariate Weibull distribution is a singular distribution, whose both the marginals are univariate Weibull distributions. This is a generalization of the Marshall-Olkin bivariate exponential distribution. The cumulative joint distribution of the Marshall-Olkin bivariate Weibull distribution is a mixture of an absolute continuous distribution function and a singular distribution function. This distribution has four unknown parameters and it is observed that the maximum likelihood estimators of the unknown parameters cannot be obtained in explicit forms. In this paper we discuss about the computation of the maximum likelihood estimators of the unknown parameters using EM algorithm. We perform some simulations to see the performances of the EM algorithm and re-analyze one data set for Illustrative Purpose.
Milind Bhanuprasad Bhatt - One of the best experts on this subject based on the ideXlab platform.
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characterization of generalized uniform distribution through expectation
Open Journal of Statistics, 2014Co-Authors: Milind Bhanuprasad BhattAbstract:Normally the mass of a root has a uniform distribution but some have different uniform distributions named Generalized Uniform Distribution (GUD). The characterization result based on expectation of function of random variable has been obtained for generalized uniform distribution. Applications are given for Illustrative Purpose including a special case of uniform distribution.
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Characterization of Power-Function Distribution through Expectation
Open Journal of Statistics, 2013Co-Authors: Milind Bhanuprasad BhattAbstract:For the characterization of the power function distribution, one needs any arbitrary non constant function only in place of independence of suitable function of order statistics, linear relation of conditional expectation, recurrence relations between expectations of function of order statistics, distributional properties of exponential distribution, record valves, lower record statistics, product of order statistics and Lorenz curve, etc. available in the literature. The goal of this research is not to give a different path-breaking approach for the characterization of power function distribution through the expectation of non constant function of random variable and provide a method to characterize the power function distribution as remark. Examples are given for the Illustrative Purpose.
Shih Toh Chang - One of the best experts on this subject based on the ideXlab platform.
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shear lag effect in simply supported prestressed concrete box girder
Journal of Bridge Engineering, 2004Co-Authors: Shih Toh ChangAbstract:In this paper, derivation and computed formulas are provided for the shear lag coefficient in a simply supported prestressed concrete box girder under dead load. In the case of prestressed tendons having parabolic configurations, formulas to compute the shear lag effect are also developed. The magnitude of upward loading intensity caused by prestress as well as the relationship between the height of the box girder and the sag of prestressed tendons have been fully treated. Conclusions are drawn that the shear lag effect caused by dead load and prestress force is equivalent to dead load acting alone, provided that the prestressed tendon is set up with a parabolic profile. Shear lag effect caused by movable load is also analyzed according to the eccentricity of the load to the half-width ratio of the box girder. Charts were prepared to predict the shear lag coefficient for live load. Finally, having considered the shear deformation of flanges, the deflection of box girders is studied for both uniformly distributed load and concentrated load. Examples are given for Illustrative Purpose.
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shear lag effect in simply supported prestressed concrete box girder
Journal of Bridge Engineering, 2004Co-Authors: Shih Toh ChangAbstract:In this paper, derivation and computed formulas are provided for the shear lag coefficient in a simply supported prestressed concrete box girder under dead load. In the case of prestressed tendons having parabolic configurations, formulas to compute the shear lag effect are also developed. The magnitude of upward loading intensity caused by prestress as well as the relationship between the height of the box girder and the sag of prestressed tendons have been fully treated. Conclusions are drawn that the shear lag effect caused by dead load and prestress force is equivalent to dead load acting alone, provided that the prestressed tendon is set up with a parabolic profile. Shear lag effect caused by movable load is also analyzed according to the eccentricity of the load to the half-width ratio of the box girder. Charts were prepared to predict the shear lag coefficient for live load. Finally, having considered the shear deformation of flanges, the deflection of box girders is studied for both uniformly distributed load and concentrated load. Examples are given for Illustrative Purpose.