To discuss the relationship between stability and bullwhip effect in the supply chain system,a basic model in a production-inventory control system is developed using difference equations.Z-transform techniques are ap...To discuss the relationship between stability and bullwhip effect in the supply chain system,a basic model in a production-inventory control system is developed using difference equations.Z-transform techniques are applied to investigate the production ordering and inventory dynamics.For the two operational regimes of sufficient inventory coverage and insufficient inventory coverage,the scope of decision parameters which make the system stable or instable is investigated.Under two operational regimes and the actual system,production release rates,stability/instability and bullwhip effect in the stable region and instable region are examined based on different demand functions,and then the numerical simulation results are given.The results show that reasonable choices of fractional adjustment of inventory and supply line can make the system stable and decrease bullwhip effect.It is summarized that the piecewise linearization based on the stability analysis approach is a valid approximation to the analysis of production-inventory ordering systems with nonlinearities.Some interesting results are obtained and they have important implications for improving inventory and order decisions in supply chain systems.展开更多
This paper extends a production-inventory model with one unreliable machine to one that hasn machines in series, separated by finite buffers. It is shown how customer service levels and otherperformance measures can b...This paper extends a production-inventory model with one unreliable machine to one that hasn machines in series, separated by finite buffers. It is shown how customer service levels and otherperformance measures can be calculated as a function of the availabilities of the machines and thesizes of the intermediate buffers.展开更多
We study a production-inventory system having a machine, a storage facility. The demand for the product is governed by an Erlangian demand arrival process, where demand sizes are independent and identically distribute...We study a production-inventory system having a machine, a storage facility. The demand for the product is governed by an Erlangian demand arrival process, where demand sizes are independent and identically distributed random variables. A two-criticalnumber policy (m, M) is used to control a machine's setups and shutdowns, namely, a machine is shut down whenever the inventory level reaches M, and resumes operating only when the inventory level falls below the critical number m(m ≤ M). We obtain the steady state distribution of the inventory process and some performance measures of the process.展开更多
This research addresses existing shortcomings in epidemic-logistics studies by emphasizing the integration of multiple models to determine optimal strategies for medical resource allocation during public health emerge...This research addresses existing shortcomings in epidemic-logistics studies by emphasizing the integration of multiple models to determine optimal strategies for medical resource allocation during public health emergencies,such as the COVID-19 outbreak.The authors develop a multi-model integrated epidemic-logistics model that seamlessly merges three specific sub-models:Optimal allocation,epidemic dynamics,and production-inventory.This model dynamically tracks the real-time varying in resource inventory levels at supply nodes and the storage capacities at transit hubs within a logistics network.Unique to the proposed research is the embedding of both the production-inventory mechanism and the impact of a social intervention(Traditional Chinese medicine as the background)within a logistics framework of resource allocation.Moreover,the authors also introduce an adaptive demand function that possesses learning ability and a probabilistic understanding,crucial for gauging real-time resource demands in affected regions.The proposed innovation extends to designing a recursive and linearizable structure,transforming the intricate multi-model system into solvable sub-models,while also offering a standardized method for creating demand functions.The numerical simulations and sensitivity analysis demonstrate the efficiency and robustness of the proposed model.The proposed framework not only enhances theoretical understandings of epidemic resource management but also provides policymakers with actionable strategies for future pandemics.展开更多
文摘To discuss the relationship between stability and bullwhip effect in the supply chain system,a basic model in a production-inventory control system is developed using difference equations.Z-transform techniques are applied to investigate the production ordering and inventory dynamics.For the two operational regimes of sufficient inventory coverage and insufficient inventory coverage,the scope of decision parameters which make the system stable or instable is investigated.Under two operational regimes and the actual system,production release rates,stability/instability and bullwhip effect in the stable region and instable region are examined based on different demand functions,and then the numerical simulation results are given.The results show that reasonable choices of fractional adjustment of inventory and supply line can make the system stable and decrease bullwhip effect.It is summarized that the piecewise linearization based on the stability analysis approach is a valid approximation to the analysis of production-inventory ordering systems with nonlinearities.Some interesting results are obtained and they have important implications for improving inventory and order decisions in supply chain systems.
文摘This paper extends a production-inventory model with one unreliable machine to one that hasn machines in series, separated by finite buffers. It is shown how customer service levels and otherperformance measures can be calculated as a function of the availabilities of the machines and thesizes of the intermediate buffers.
基金This research is supported by the National Natural Science Foundation of China (No. 19871093).
文摘We study a production-inventory system having a machine, a storage facility. The demand for the product is governed by an Erlangian demand arrival process, where demand sizes are independent and identically distributed random variables. A two-criticalnumber policy (m, M) is used to control a machine's setups and shutdowns, namely, a machine is shut down whenever the inventory level reaches M, and resumes operating only when the inventory level falls below the critical number m(m ≤ M). We obtain the steady state distribution of the inventory process and some performance measures of the process.
基金supported by the National Natural Science Foundation of China under Grant Nos.71871136 and 11571008。
文摘This research addresses existing shortcomings in epidemic-logistics studies by emphasizing the integration of multiple models to determine optimal strategies for medical resource allocation during public health emergencies,such as the COVID-19 outbreak.The authors develop a multi-model integrated epidemic-logistics model that seamlessly merges three specific sub-models:Optimal allocation,epidemic dynamics,and production-inventory.This model dynamically tracks the real-time varying in resource inventory levels at supply nodes and the storage capacities at transit hubs within a logistics network.Unique to the proposed research is the embedding of both the production-inventory mechanism and the impact of a social intervention(Traditional Chinese medicine as the background)within a logistics framework of resource allocation.Moreover,the authors also introduce an adaptive demand function that possesses learning ability and a probabilistic understanding,crucial for gauging real-time resource demands in affected regions.The proposed innovation extends to designing a recursive and linearizable structure,transforming the intricate multi-model system into solvable sub-models,while also offering a standardized method for creating demand functions.The numerical simulations and sensitivity analysis demonstrate the efficiency and robustness of the proposed model.The proposed framework not only enhances theoretical understandings of epidemic resource management but also provides policymakers with actionable strategies for future pandemics.
