Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at...Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at each iteration by incorporating adaptive parameter selection and a more general subgradient projection operator. The advantages of the proposed method are highlighted by the proof of strong convergence presented in the paper. Several concrete examples are given to demonstrate the effectiveness of the algorithm, with comparisons illustrating its superior CPU running time compared to alternative techniques. The practical applicability of the algorithm is also demonstrated by applying it to a realistic supply chain network model.展开更多
This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In...This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In view of different models,corresponding suggestions are put forward to ensure the quality safety of agricultural products in Heilongjiang Province.展开更多
Considering the harder and harder competition among enterprises, this paper puts forward the Resource model of supply chain （RBV） to enhance competitive advantages, then analyses the source of supply chain competiti...Considering the harder and harder competition among enterprises, this paper puts forward the Resource model of supply chain （RBV） to enhance competitive advantages, then analyses the source of supply chain competitive advantages and introduce the advantage formula. Finally, the rent contribution to supply chain management is explained in detail.展开更多
To solve the inventory coordination model in a multi-stage, multi-customer supply chain, this paper first analyzes the third model （integer powers of two multipliers at each firm） studied by Moutaz Khouja （2003）, ...To solve the inventory coordination model in a multi-stage, multi-customer supply chain, this paper first analyzes the third model （integer powers of two multipliers at each firm） studied by Moutaz Khouja （2003）, and the authors take a numerical example to prove that the third model is irrational to miss feasible solution. Then this paper puts up a new improved model （integer multiplier at each firm）, and takes the example to prove it gives better results than the integer powers of two multipliers at each firm.展开更多
With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the par...With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference （SCOR） model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.展开更多
To meet the demands of rapid development of the automotive industry, a well-built supply chain system is needed urgently under the background of globalization. The implication of Global Supply Chain（GSC） is discusse...To meet the demands of rapid development of the automotive industry, a well-built supply chain system is needed urgently under the background of globalization. The implication of Global Supply Chain（GSC） is discussed at first. Then, three characteristics of global automobile supply chain such us reversibility, complexity, and synergy are analyzed, and accordingly three apocalypses related global auto supply chain are proposed.展开更多
In order to analyze the effects of different cooperative mechanisms between a mobile device manufacturer and a mobile network operator （ MNO ）, a Stackelberg structure is constructed. The manufacturer acts as a lead...In order to analyze the effects of different cooperative mechanisms between a mobile device manufacturer and a mobile network operator （ MNO ）, a Stackelberg structure is constructed. The manufacturer acts as a leader, while the MNO acts as a follower, i. e., a traditional retailer. Three cooperative mechanisms are considered： the manufacturer does not invest in developing the propriety function and software to support the infrastructure capacity of the MNO; the manufacturer invests in the development; the MNO offers a subsidy to encourage the manufacturer to invest in development. The results reveal that investing in the development can increase the profits of both the manufacturer and the MNO. Furthermore, if the MNO shares certain investment costs with the manufacturer, the MNO may charge higher prices of mobile connection services and mobile value-added services, and the profits of the two players may be enhanced.展开更多
Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber r...Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.展开更多
In addition to maximizing economic benefits, reverse supply chains should further seek to maximize social benefits by increasing the quantity of waste electrical and electronic equipment （WEEE）. The paper investigat...In addition to maximizing economic benefits, reverse supply chains should further seek to maximize social benefits by increasing the quantity of waste electrical and electronic equipment （WEEE）. The paper investigates cooperative models with different parties in a three-echelon reverse supply chain for WEEE consisting of a single collector, a single remanufacturer, and two retailers based on complete information. In acldition, the optimal decisions of four cooperative models and the effect of the market demand of remanufactured WEEE products and the market share of two retailers on the optimal decisions are discussed. The results indicate that optimal total channel profit and recycle quantity in a reverse supply chain are maximized in a centralized model. The optimal total channel profit and recycle quantity increase with an increase in the market demand of remanufactured WEEE products. The three-echelon reverse supply chain consisting of duopolistic retailers maximizes total channel profit and recycle quantity in a reverse supply chain fbr WEEE.展开更多
Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber r...Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.展开更多
Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and beh...Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.展开更多
文摘Using a modified subgradient extragradient algorithm, this paper proposed a novel approach to solving a supply chain network equilibrium model. The method extends the scope of optimisation and improves the accuracy at each iteration by incorporating adaptive parameter selection and a more general subgradient projection operator. The advantages of the proposed method are highlighted by the proof of strong convergence presented in the paper. Several concrete examples are given to demonstrate the effectiveness of the algorithm, with comparisons illustrating its superior CPU running time compared to alternative techniques. The practical applicability of the algorithm is also demonstrated by applying it to a realistic supply chain network model.
基金Supported by Ministry of Education Humanities and Social Sciences Foundation (10YJA630070)
文摘This paper analyses the supply chain models of four types of agricultural products,namely fruits and vegetables,poultry,aquatic products and dairy,and the food safety problems arising from the links of supply chain.In view of different models,corresponding suggestions are put forward to ensure the quality safety of agricultural products in Heilongjiang Province.
文摘Considering the harder and harder competition among enterprises, this paper puts forward the Resource model of supply chain （RBV） to enhance competitive advantages, then analyses the source of supply chain competitive advantages and introduce the advantage formula. Finally, the rent contribution to supply chain management is explained in detail.
文摘To solve the inventory coordination model in a multi-stage, multi-customer supply chain, this paper first analyzes the third model （integer powers of two multipliers at each firm） studied by Moutaz Khouja （2003）, and the authors take a numerical example to prove that the third model is irrational to miss feasible solution. Then this paper puts up a new improved model （integer multiplier at each firm）, and takes the example to prove it gives better results than the integer powers of two multipliers at each firm.
文摘With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference （SCOR） model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.
基金supported by Humanities and Social Sciences Foundation of Anhui Province under Grant No. 2006SK213Anhui Province Youth Foundation under Grant No. 2008jqw076Anhui University of Technology and Science Youth Foundation under Grant No.2004YQ013
文摘To meet the demands of rapid development of the automotive industry, a well-built supply chain system is needed urgently under the background of globalization. The implication of Global Supply Chain（GSC） is discussed at first. Then, three characteristics of global automobile supply chain such us reversibility, complexity, and synergy are analyzed, and accordingly three apocalypses related global auto supply chain are proposed.
文摘In order to analyze the effects of different cooperative mechanisms between a mobile device manufacturer and a mobile network operator （ MNO ）, a Stackelberg structure is constructed. The manufacturer acts as a leader, while the MNO acts as a follower, i. e., a traditional retailer. Three cooperative mechanisms are considered： the manufacturer does not invest in developing the propriety function and software to support the infrastructure capacity of the MNO; the manufacturer invests in the development; the MNO offers a subsidy to encourage the manufacturer to invest in development. The results reveal that investing in the development can increase the profits of both the manufacturer and the MNO. Furthermore, if the MNO shares certain investment costs with the manufacturer, the MNO may charge higher prices of mobile connection services and mobile value-added services, and the profits of the two players may be enhanced.
基金This work was funded by the UK EPSRC[grant number:EP/S035362/1,EP/N023013/1,EP/N02334X/1]and by the Cisco Research Centre[grant number 1525381].
文摘Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.
基金This work was supported by the National Natural Science Foundation of China （Grant No. 71471105）.
文摘In addition to maximizing economic benefits, reverse supply chains should further seek to maximize social benefits by increasing the quantity of waste electrical and electronic equipment （WEEE）. The paper investigates cooperative models with different parties in a three-echelon reverse supply chain for WEEE consisting of a single collector, a single remanufacturer, and two retailers based on complete information. In acldition, the optimal decisions of four cooperative models and the effect of the market demand of remanufactured WEEE products and the market share of two retailers on the optimal decisions are discussed. The results indicate that optimal total channel profit and recycle quantity in a reverse supply chain are maximized in a centralized model. The optimal total channel profit and recycle quantity increase with an increase in the market demand of remanufactured WEEE products. The three-echelon reverse supply chain consisting of duopolistic retailers maximizes total channel profit and recycle quantity in a reverse supply chain fbr WEEE.
基金funded by the UK EPSRC[grant number:EP/S035362/1,EP/N023013/1,EP/N02334X/1]by the Cisco Research Centre[grant number 1525381].
文摘Digital technologies have changed the way supply chain operations are structured.In this article,we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks.A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0,with a specific focus on the mitigation of cyber risks.An analytical framework is presented,based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies.This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning(AI/ML)and real-time intelligence for predictive cyber risk analytics.The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge.This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed,and when AI/ML technologies are migrated to the periphery of IoT networks.
文摘Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.
