Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts.However,the particular impact of meteorological foreca...Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts.However,the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known.In this study,a series of forecasts with different forecast lead times for January,April,July,and October of 2018 are conducted over the Beijing-Tianjin-Hebei(BTH)region and the impacts of meteorological forecasting uncertainties on surface PM_(2.5)concentration forecasts with each lead time are investigated.With increased lead time,the forecasted PM_(2.5)concentrations significantly change and demonstrate obvious seasonal variations.In general,the forecasting uncertainties in monthly mean surface PM_(2.5)concentrations in the BTH region due to lead time are the largest(80%)in spring,followed by autumn(~50%),summer(~40%),and winter(20%).In winter,the forecasting uncertainties in total surface PM_(2.5)mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles.In spring,the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds,thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust.In summer,the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates,which are associated with the reduction of near-surface wind speed and precipitation rate.In autumn,the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles,which is associated with changes in the large-scale circulation.展开更多
In order to let the supplier make more reasonable supply decisions,an integrated continuous replenishment policy for the vendor-managed inventory system is presented,which considers the quantity-based shipment consoli...In order to let the supplier make more reasonable supply decisions,an integrated continuous replenishment policy for the vendor-managed inventory system is presented,which considers the quantity-based shipment consolidation and stock replenishment with lead time.Then the system cost is analyzed and a mathematical model is built.Since the model is rather complex,the bounds of the optimal policy are first attained,then the problem is solved by a heuristic algorithm.Through experiments the relationship between the order lead time and the corresponding integrated policy is discussed,and the influence on the system cost is also analyzed.The results reveal that the lead time's influence on the system is more serious with the increase of the order lead time,the integrated policy with the order lead time is more reasonable and the optimal policy can minimize the total system cost.Finally,the parameter sensitivity of the model is analyzed.展开更多
The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was e...The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was established and based on relevant analysis,the original model could be transformed by minimax method.Then,the optimal order quantity and production quantity influenced by service level constraint were analyzed and the boundary of optimal order quantity and production quantity was given.According to this boundary,the effective method and tactics were put forward to solve the transformed model.In case analysis,the optimal expected total cost of two-echelon inventory can be obtained and it was analyzed how service level constraint and safety factor influence the optimal expected total cost of two-echelon inventory.The results show that the optimal expected total cost of two-echelon inventory is constrained by the higher constraint between service level constraint and safety factor.展开更多
As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time de...As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.展开更多
Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to thos...Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to those from a shop with one-piece transfer lots. Next, a mathematical programming model for minimizing lead time in the mixed-model job shop is presented, in which one-piece transfer lots are used. Key factors affecting lead time are found by analyzing the sum of the longest setup time of individual items among the shared processes （SLST） and the longest processing time of individual items among processes （LPT）. And lead time can be minimized by cutting down the SLST and LPT. Reduction of the SLST is described as a traveling salesman problem （TSP）, and the minimum of the SLST is solved through job shop scheduling. Removing the bottleneck and leveling the production line optimize the LPT. If the number of items produced is small, the routings are relatively short, and items and facilities are changed infrequently, the optimal schedule will remain valid. Finally a brief example serves to illustrate the method.展开更多
In fixed order quantity systems,uncertainty in lead time is expressed as a set of scenarios with occurrence probabilities,and the mean and variance in demand distribution are supposed to be changeable according to a k...In fixed order quantity systems,uncertainty in lead time is expressed as a set of scenarios with occurrence probabilities,and the mean and variance in demand distribution are supposed to be changeable according to a known pattern.A new concept of "dynamic robust optimal reorder point" is proposed in this paper and its value is calculated as a "robust optimal reorder point function with respect to reorder time".Two approaches were employed in determining the dynamic optimal reorder point.The first is a shortage rate satisfaction approach and the second is a backorder cost minimization approach.The former aims at finding the minimum value of reorder point at each reorder time which satisfies the condition that the cumulative distribution function (CDF) of shortage rate under a given set of scenarios in lead time is greater than or equal to a basic CDF of shortage rate predetermined by a decision-maker.In the latter approach,the CDF of closeness of reorder point is defined at each reorder time to express how close to the optimal reorder points under the set of scenarios,and the dynamic optimal reorder point is defined according to stochastic ordering.Some numerical examples demonstrate the features of these dynamic robust optimal reorder points.展开更多
To encourage retailers to form cooperative alliances to jointly replenish inventory,considering that the supplier provides a flexible lead time and quantity discount to retailers,a model of average total cost per unit...To encourage retailers to form cooperative alliances to jointly replenish inventory,considering that the supplier provides a flexible lead time and quantity discount to retailers,a model of average total cost per unit time of periodic joint replenishment is constructed,and an approximate algorithm,which can satisfy the requirement of any given precision,is given.The cost allocation rule in the core of the joint replenishment game is designed based on the cooperative game theory.The numerical experiment results show that the proposed algorithm can quickly solve the joint replenishment problem when the item number is not greater than 640.The retailer's cost saving rate is always greater than 0,and it increases with the increase in quantity discount and fixed cost after adopting the given cost allocation rule.With the increase in the safety stock level,the retailer's cost saving rate increases first and then decreases;and the retailer's cost saving rate increases with the increase in the size of the alliance,but it decreases as the number of product category increases.The proposed cost allocation rule can reduce the retailer's cost up to 20%,which is conducive to forming a cooperative coalition.展开更多
This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF)for heavy-rainfall events over south China during the rainy seasons...This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF)for heavy-rainfall events over south China during the rainy seasons in 2013-2020.The control experiment,where the analysis-forecast cycles run with model resolutions of about 3 km,was compared to a lower-resolution experiment with model resolutions of about 9 km,and a longer-term experiment activated 12 hours earlier.Rainfall forecasting in the presummer rainy season was significantly improved by improving model resolutions,with more improvements in cases with stronger synoptic-scale forcings.This is partially attributed to the improved initial conditions(ICs)and subsequent forecasts for low-level jets(LLJs).Forecasts of heavy rainfall induced by landfalling tropical cyclones(TCs)benefited from increasing model resolutions in the first 6 hours.Forecast improvements in rainfall due to shortening forecast lead times were more significant at earlier(1-6 h)and later(7-12 h)lead times for cases with stronger and weaker synoptic-scale forcings,respectively,due to the area-and case-dependent improvements in ICs for nonprecipitation variables.Specifically,significant improvements mainly presented over the northern South China Sea for low-level onshore wind of weak-forcing cases but over south China for LLJs of strong-forcing cases during the presummer rainy season,and over south China for all the nonprecipitation variables above the surface during the TC season.However,some disadvantages of higher-resolution and shorter-term forecasts in QPFs highlight the importance of developing ensemble forecasting with proper IC perturbations,which include the complementary advantages of lower-resolution and longer-term forecasts.展开更多
The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may ...The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may cause severe property damage and even loss of human life.Nevertheless,there is a lack of studies that evaluate the performance of the numerical weather prediction(NWP)models such as weather research and forecasting(WRF)model in anticipating this type of weather in the region.This study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer(PBL)and microphysics parameterization schemes under varied lead times in predicting an extreme wind event(gusts>30 m s^(-1))in Central Argentina.The results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme event.It is found that no single combination outperforms the others,although there is a slight tendency for Combination A,which utilizes the Mellor-Yamada-Janjic(MYJ)parameterization for the PBL and the Eta similarity parameterization for the surface layer,to more accurately capture the extreme wind speed.Compared with wind gust observations at five weather stations,the wind gust parameterization predicted the intensity and occurrence time of the peak wind,with an acceptable bias(time of peak<±1 h).Analysis of grid configurations(resolutions of 4 vs 9/3/1 km)revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular event.With regard to lead time,a shorter lead time does not necessarily result in more accurate forecasts.Nevertheless,it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.展开更多
This paper deals with the problem of planned lead time calculation in a Material Requirement Planning （MRP） environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging co...This paper deals with the problem of planned lead time calculation in a Material Requirement Planning （MRP） environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered： multi-level serial-production and assembly systems. For the serial production systems （one type of component at each level）, a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and se＇~eral numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.展开更多
This study deals an integrated manufacturer-buyer supply chain system for imperfect production under stochastic lead time demand.Here,defective rate has been followed as a function of production rate.Also,the produced...This study deals an integrated manufacturer-buyer supply chain system for imperfect production under stochastic lead time demand.Here,defective rate has been followed as a function of production rate.Also,the produced units have been inspected in order to screen the defective units but screening rate is less than the production rate and greater than the demand rate.Buyer purchases the products from the manufacturer.Also,we assume that shortage during the lead time is permitted and demand during the shortage period is fully backordered.The objective is to derive the optimal production rate,ordering quantity and to maximize joint total profit.Basically,two different models for different probability distribution functions of stochastic lead time demand have been developed.Some numerical examples are provided to show the applicability of the proposed models comparing the optimum average profits.Finally,sensitive analysis,conclusion and future researches are presented.展开更多
We consider a joint inventory-pricing control problem in a single-product,periodic-review,dual-supplier inventory system.The two suppliers have different lead times.One expedited supplier offers instantaneous replenis...We consider a joint inventory-pricing control problem in a single-product,periodic-review,dual-supplier inventory system.The two suppliers have different lead times.One expedited supplier offers instantaneous replenishment,and one regular supplier requires an L-period lead time for delivery.The supply quantity is stochastic and the demand is price-dependent.For the expedited inventory replenishment,we characterize the optimal policy as a state-dependent almost-threshold policy by extending the stochastically linear in mid-point to a multidimensional setting.To investigate the optimal regular inventory replenishment and pricing policy,we propose the notions of partially stochastic translation(PST)and increasing partially stochastic translation(IPST),which help in obtaining the antimultimodularity preservation in dynamic programming problems.We provide properties,sufficient conditions,and examples for PST and IPST functions.By applying PST and IPST,we obtain the antimultimodularity of the profit functions.The antimultimodular profit functions ensure that the optimal regular ordering quantity and the optimal price are monotone in the current inventory level and outstanding order quantities.Moreover,we reveal that as the time interval increases,the effects of previous outstanding orders on the optimal regular ordering and pricing decisions are decreasing and increasing,respectively.PST and IPST also enable us to further characterize the optimal expedited ordering quantity as decreasing in the inventory level.However,the optimal expedited ordering quantity can be non-monotone with respect to the outstanding order quantities,as shown in the example.展开更多
The mathematical model of the demander versus supplier has been presented by adopting optimization theories, the economical order quantity （EOQ） and economic production quantity （EPQ） has further been studied. The...The mathematical model of the demander versus supplier has been presented by adopting optimization theories, the economical order quantity （EOQ） and economic production quantity （EPQ） has further been studied. Then under the consideration of Pareto optimization, a joint decision model of price and lead time discount and lot size has been presented. Further more the sensitive analysis of price and lead time discount are analyzed with an empirical example.展开更多
This article considers the two-level supply chain model incorporating an imperfect production process under a variable lead time.The cost of producing a unit item is calculated as a function of the production rate.In ...This article considers the two-level supply chain model incorporating an imperfect production process under a variable lead time.The cost of producing a unit item is calculated as a function of the production rate.In addition,two alternative production functions(linear and quadratic functions)are used to relate process quality and production rate.Lead time demand follows two different distributions,based on which two mathematical formulations are described in this paper.In the first model,the lead time demand follows a normal distribution.In the second model,the lead time demand doesn’t follow any particular distribution,but the mean and the standard deviation are known.The lead time length is minimized by incorporating the lead time crashing cost.This research aims to analyze the optimized total cost of the supply chain under two different distributions.展开更多
The objective of this paper is to derive the analytical solution of the EOQ model of multiple items with both demand-dependent unit cost and leading time using geometric programming approach. The varying purchase and ...The objective of this paper is to derive the analytical solution of the EOQ model of multiple items with both demand-dependent unit cost and leading time using geometric programming approach. The varying purchase and leading time crashing costs are considered to be continuous functions of demand rate and leading time, respectively. The researchers deduce the optimal order quantity, the demand rate and the leading time as decision variables then the optimal total cost is obtained.展开更多
Climatic variability influences the hydrological cycle that subsequently affects the discharge in the stream. The variability in the climate can be represented by the ocean-atmospheric oscillations which provide the f...Climatic variability influences the hydrological cycle that subsequently affects the discharge in the stream. The variability in the climate can be represented by the ocean-atmospheric oscillations which provide the forecast opportunity for the streamflow. Prediction of future water availability accurately and reliably is a key step for successful water resource management in the arid regions. Four popular ocean-atmospheric indices were used in this study for annual streamflow volume prediction. They were Pacific Decadal Oscillation (PDO), El-Nino Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). Multivariate Relevance Vector Machine (MVRVM), a data driven model based on Bayesian learning approach was used as a prediction model. The model was applied to four unimpaired stream gages in Utah that spatially covers the state from north to south. Different models were developed based on the combinations of oscillation indices in the input. A total of 60 years (1950-2009) of data were used for the analysis. The model was trained on 50 years of data (1950-1999) and tested on 10 years of data (2000-2009). The best combination of oscillation indices and the lead-time were identified for each gage which was used to develop the prediction model. The predicted flow had reasonable agreement with the actual annual flow volume. The sensitivity analysis shows that the PDO and ENSO have relatively stronger effect compared to other oscillation indices in Utah. The prediction results from the MVRVM were compared with the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) where MVRVM performed relatively better.展开更多
基金supported by the National Key Research and Development Program of China(No.2022YFC3700701)National Natural Science Foundation of China(Grant Nos.41775146,42061134009)+1 种基金USTC Research Funds of the Double First-Class Initiative(YD2080002007)Strategic Priority Research Program of Chinese Academy of Sciences(XDB41000000).
文摘Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts.However,the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known.In this study,a series of forecasts with different forecast lead times for January,April,July,and October of 2018 are conducted over the Beijing-Tianjin-Hebei(BTH)region and the impacts of meteorological forecasting uncertainties on surface PM_(2.5)concentration forecasts with each lead time are investigated.With increased lead time,the forecasted PM_(2.5)concentrations significantly change and demonstrate obvious seasonal variations.In general,the forecasting uncertainties in monthly mean surface PM_(2.5)concentrations in the BTH region due to lead time are the largest(80%)in spring,followed by autumn(~50%),summer(~40%),and winter(20%).In winter,the forecasting uncertainties in total surface PM_(2.5)mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles.In spring,the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds,thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust.In summer,the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates,which are associated with the reduction of near-surface wind speed and precipitation rate.In autumn,the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles,which is associated with changes in the large-scale circulation.
基金The National Key Technology R&D Program of China during the 11 th Five-Year Plan Period(No.2006BAH02A06)
文摘In order to let the supplier make more reasonable supply decisions,an integrated continuous replenishment policy for the vendor-managed inventory system is presented,which considers the quantity-based shipment consolidation and stock replenishment with lead time.Then the system cost is analyzed and a mathematical model is built.Since the model is rather complex,the bounds of the optimal policy are first attained,then the problem is solved by a heuristic algorithm.Through experiments the relationship between the order lead time and the corresponding integrated policy is discussed,and the influence on the system cost is also analyzed.The results reveal that the lead time's influence on the system is more serious with the increase of the order lead time,the integrated policy with the order lead time is more reasonable and the optimal policy can minimize the total system cost.Finally,the parameter sensitivity of the model is analyzed.
基金Project(71102174,71372019)supported by the National Natural Science Foundation of ChinaProject(9123028)supported by the Beijing Natural Science Foundation of China+3 种基金Project(20111101120019)supported by the Specialized Research Fund for Doctoral Program of Higher Education of ChinaProject(11JGC106)supported by the Beijing Philosophy&Social Science Foundation of ChinaProjects(NCET-10-0048,NCET-10-0043)supported by the Program for New Century Excellent Talents in University of ChinaProject(2010YC1307)supported by Excellent Young Teacher in Beijing Institute of Technology of China
文摘The decision-making and optimization of two-echelon inventory coordination were analyzed with service level constraint and controllable lead time sensitive to order quantity.First,the basic model of this problem was established and based on relevant analysis,the original model could be transformed by minimax method.Then,the optimal order quantity and production quantity influenced by service level constraint were analyzed and the boundary of optimal order quantity and production quantity was given.According to this boundary,the effective method and tactics were put forward to solve the transformed model.In case analysis,the optimal expected total cost of two-echelon inventory can be obtained and it was analyzed how service level constraint and safety factor influence the optimal expected total cost of two-echelon inventory.The results show that the optimal expected total cost of two-echelon inventory is constrained by the higher constraint between service level constraint and safety factor.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2007AA04Z102)the National Natural Science Foundation of China(6087407160574077).
文摘As one of the basic inventory cost models, the （Q, τ）inventory cost model of dual suppliers with random procurement lead time is mostly formulated by using the concepts of ＂effective lead time＂ and ＂lead time demand＂, which may lead to an imprecise inventory cost. Through the real-time statistic of the inventory quantities, this paper considers the precise （Q, τ） inventory cost model of dual supplier procurement by using an infinitesimal dividing method. The traditional modeling method of the inventory cost for dual supplier procurement includes complex procedures. To reduce the complexity effectively, the presented method investigates the statistics properties in real-time of the inventory quantities with the application of the infinitesimal dividing method. It is proved that the optimal holding and shortage costs of dual supplier procurement are less than those of single supplier procurement respectively. With the assumption that both suppliers have the same distribution of lead times, the convexity of the cost function per unit time is proved. So the optimal solution can be easily obtained by applying the classical convex optimization methods. The numerical examples are given to verify the main conclusions.
基金This project is supported by National Natural Science Foundation of China (No.70372062, No.70572044)Program for New Century Excellent Talents in University of China (No.NCET-04-0240).
文摘Firstly an overview of the potential impact on work-in-process （WIP） and lead time is provided when transfer lot sizes are undifferentiated from processing lot sizes. Simple performance examples are compared to those from a shop with one-piece transfer lots. Next, a mathematical programming model for minimizing lead time in the mixed-model job shop is presented, in which one-piece transfer lots are used. Key factors affecting lead time are found by analyzing the sum of the longest setup time of individual items among the shared processes （SLST） and the longest processing time of individual items among processes （LPT）. And lead time can be minimized by cutting down the SLST and LPT. Reduction of the SLST is described as a traveling salesman problem （TSP）, and the minimum of the SLST is solved through job shop scheduling. Removing the bottleneck and leveling the production line optimize the LPT. If the number of items produced is small, the routings are relatively short, and items and facilities are changed infrequently, the optimal schedule will remain valid. Finally a brief example serves to illustrate the method.
基金Project (No.21510152) supported by the Grant-in-Aid for Scientific Research (C),Japan
文摘In fixed order quantity systems,uncertainty in lead time is expressed as a set of scenarios with occurrence probabilities,and the mean and variance in demand distribution are supposed to be changeable according to a known pattern.A new concept of "dynamic robust optimal reorder point" is proposed in this paper and its value is calculated as a "robust optimal reorder point function with respect to reorder time".Two approaches were employed in determining the dynamic optimal reorder point.The first is a shortage rate satisfaction approach and the second is a backorder cost minimization approach.The former aims at finding the minimum value of reorder point at each reorder time which satisfies the condition that the cumulative distribution function (CDF) of shortage rate under a given set of scenarios in lead time is greater than or equal to a basic CDF of shortage rate predetermined by a decision-maker.In the latter approach,the CDF of closeness of reorder point is defined at each reorder time to express how close to the optimal reorder points under the set of scenarios,and the dynamic optimal reorder point is defined according to stochastic ordering.Some numerical examples demonstrate the features of these dynamic robust optimal reorder points.
基金The National Natural Science Foundation of China(No.71531004).
文摘To encourage retailers to form cooperative alliances to jointly replenish inventory,considering that the supplier provides a flexible lead time and quantity discount to retailers,a model of average total cost per unit time of periodic joint replenishment is constructed,and an approximate algorithm,which can satisfy the requirement of any given precision,is given.The cost allocation rule in the core of the joint replenishment game is designed based on the cooperative game theory.The numerical experiment results show that the proposed algorithm can quickly solve the joint replenishment problem when the item number is not greater than 640.The retailer's cost saving rate is always greater than 0,and it increases with the increase in quantity discount and fixed cost after adopting the given cost allocation rule.With the increase in the safety stock level,the retailer's cost saving rate increases first and then decreases;and the retailer's cost saving rate increases with the increase in the size of the alliance,but it decreases as the number of product category increases.The proposed cost allocation rule can reduce the retailer's cost up to 20%,which is conducive to forming a cooperative coalition.
基金National Key Research and Development Program of China(2017YFC1501603)National Natural Science Foundation of China(41975136,42075014)+2 种基金Startup Foundation for Introducing Talent of NUIST(2023r121)Guangdong Basic and Applied Basic Research Foundation(2019A1515011118)Guangzhou Municipal Science and Technology Planning Project of China(202103000030)。
文摘This study investigated the impacts of increasing model resolutions and shortening forecast lead times on the quantitative precipitation forecast(QPF)for heavy-rainfall events over south China during the rainy seasons in 2013-2020.The control experiment,where the analysis-forecast cycles run with model resolutions of about 3 km,was compared to a lower-resolution experiment with model resolutions of about 9 km,and a longer-term experiment activated 12 hours earlier.Rainfall forecasting in the presummer rainy season was significantly improved by improving model resolutions,with more improvements in cases with stronger synoptic-scale forcings.This is partially attributed to the improved initial conditions(ICs)and subsequent forecasts for low-level jets(LLJs).Forecasts of heavy rainfall induced by landfalling tropical cyclones(TCs)benefited from increasing model resolutions in the first 6 hours.Forecast improvements in rainfall due to shortening forecast lead times were more significant at earlier(1-6 h)and later(7-12 h)lead times for cases with stronger and weaker synoptic-scale forcings,respectively,due to the area-and case-dependent improvements in ICs for nonprecipitation variables.Specifically,significant improvements mainly presented over the northern South China Sea for low-level onshore wind of weak-forcing cases but over south China for LLJs of strong-forcing cases during the presummer rainy season,and over south China for all the nonprecipitation variables above the surface during the TC season.However,some disadvantages of higher-resolution and shorter-term forecasts in QPFs highlight the importance of developing ensemble forecasting with proper IC perturbations,which include the complementary advantages of lower-resolution and longer-term forecasts.
基金Supported by the Hydrometeorological Observatory of the Province of Córdoba(OHMC),the Ministry of Public Services of the Province of Córdoba.
文摘The central region of Argentina is known to be a source of some most extreme weather events in the world,which are partially associated with the passage of cold fronts accompanied often by extreme wind gusts.This may cause severe property damage and even loss of human life.Nevertheless,there is a lack of studies that evaluate the performance of the numerical weather prediction(NWP)models such as weather research and forecasting(WRF)model in anticipating this type of weather in the region.This study compares the performance of the operational WRF in Argentina using four combinations of various planetary boundary layer(PBL)and microphysics parameterization schemes under varied lead times in predicting an extreme wind event(gusts>30 m s^(-1))in Central Argentina.The results demonstrate that the WRF model is capable of providing an acceptable prediction of wind speed during an extreme event.It is found that no single combination outperforms the others,although there is a slight tendency for Combination A,which utilizes the Mellor-Yamada-Janjic(MYJ)parameterization for the PBL and the Eta similarity parameterization for the surface layer,to more accurately capture the extreme wind speed.Compared with wind gust observations at five weather stations,the wind gust parameterization predicted the intensity and occurrence time of the peak wind,with an acceptable bias(time of peak<±1 h).Analysis of grid configurations(resolutions of 4 vs 9/3/1 km)revealed that higher resolution does not imply an improvement in the wind gust forecast for this particular event.With regard to lead time,a shorter lead time does not necessarily result in more accurate forecasts.Nevertheless,it is beneficial to conduct multiple sensitivity runs in order to obtain and understand the dispersion of forecasted wind speeds.
文摘This paper deals with the problem of planned lead time calculation in a Material Requirement Planning （MRP） environment under stochastic lead times. The objective is to minimize the sum of holding and backlogging costs. The proposed approach is based on discrete time inventory control where the decision variables are integer. Two types of systems are considered： multi-level serial-production and assembly systems. For the serial production systems （one type of component at each level）, a mathematical model is suggested. Then, it is proven that this model is equivalent to the well known discrete Newsboy Model. This directly provides the optimal values for the planned lead times. For multilevel assembly systems, a dedicated model is proposed and some properties of the decision variables and objective function are proven. These properties are used to calculate lower and upper limits on the decision variables and lower and upper bounds on the objective function. The obtained limits and bounds open the possibility to develop an efficient optimization algorithm using, for example, a Branch and Bound approach. The paper presents the proposed models in detail with corresponding proofs and se＇~eral numerical examples. Some advantages of the suggested models and perspectives of this research are discussed.
文摘This study deals an integrated manufacturer-buyer supply chain system for imperfect production under stochastic lead time demand.Here,defective rate has been followed as a function of production rate.Also,the produced units have been inspected in order to screen the defective units but screening rate is less than the production rate and greater than the demand rate.Buyer purchases the products from the manufacturer.Also,we assume that shortage during the lead time is permitted and demand during the shortage period is fully backordered.The objective is to derive the optimal production rate,ordering quantity and to maximize joint total profit.Basically,two different models for different probability distribution functions of stochastic lead time demand have been developed.Some numerical examples are provided to show the applicability of the proposed models comparing the optimum average profits.Finally,sensitive analysis,conclusion and future researches are presented.
基金supported in part by NSFC 72001198,71731010,71988101,and 71991464/71991460the National Key R&D Program of China(2020AAA0103804/2020AAA0103800)+2 种基金the Fundamental Research Funds for the Central Universities(WK2040000027)USTC Research Funds of the Double First-Class Initiative(YD2040002004)GRF Grant 115080/17
文摘We consider a joint inventory-pricing control problem in a single-product,periodic-review,dual-supplier inventory system.The two suppliers have different lead times.One expedited supplier offers instantaneous replenishment,and one regular supplier requires an L-period lead time for delivery.The supply quantity is stochastic and the demand is price-dependent.For the expedited inventory replenishment,we characterize the optimal policy as a state-dependent almost-threshold policy by extending the stochastically linear in mid-point to a multidimensional setting.To investigate the optimal regular inventory replenishment and pricing policy,we propose the notions of partially stochastic translation(PST)and increasing partially stochastic translation(IPST),which help in obtaining the antimultimodularity preservation in dynamic programming problems.We provide properties,sufficient conditions,and examples for PST and IPST functions.By applying PST and IPST,we obtain the antimultimodularity of the profit functions.The antimultimodular profit functions ensure that the optimal regular ordering quantity and the optimal price are monotone in the current inventory level and outstanding order quantities.Moreover,we reveal that as the time interval increases,the effects of previous outstanding orders on the optimal regular ordering and pricing decisions are decreasing and increasing,respectively.PST and IPST also enable us to further characterize the optimal expedited ordering quantity as decreasing in the inventory level.However,the optimal expedited ordering quantity can be non-monotone with respect to the outstanding order quantities,as shown in the example.
文摘The mathematical model of the demander versus supplier has been presented by adopting optimization theories, the economical order quantity （EOQ） and economic production quantity （EPQ） has further been studied. Then under the consideration of Pareto optimization, a joint decision model of price and lead time discount and lot size has been presented. Further more the sensitive analysis of price and lead time discount are analyzed with an empirical example.
文摘This article considers the two-level supply chain model incorporating an imperfect production process under a variable lead time.The cost of producing a unit item is calculated as a function of the production rate.In addition,two alternative production functions(linear and quadratic functions)are used to relate process quality and production rate.Lead time demand follows two different distributions,based on which two mathematical formulations are described in this paper.In the first model,the lead time demand follows a normal distribution.In the second model,the lead time demand doesn’t follow any particular distribution,but the mean and the standard deviation are known.The lead time length is minimized by incorporating the lead time crashing cost.This research aims to analyze the optimized total cost of the supply chain under two different distributions.
文摘The objective of this paper is to derive the analytical solution of the EOQ model of multiple items with both demand-dependent unit cost and leading time using geometric programming approach. The varying purchase and leading time crashing costs are considered to be continuous functions of demand rate and leading time, respectively. The researchers deduce the optimal order quantity, the demand rate and the leading time as decision variables then the optimal total cost is obtained.
文摘Climatic variability influences the hydrological cycle that subsequently affects the discharge in the stream. The variability in the climate can be represented by the ocean-atmospheric oscillations which provide the forecast opportunity for the streamflow. Prediction of future water availability accurately and reliably is a key step for successful water resource management in the arid regions. Four popular ocean-atmospheric indices were used in this study for annual streamflow volume prediction. They were Pacific Decadal Oscillation (PDO), El-Nino Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO). Multivariate Relevance Vector Machine (MVRVM), a data driven model based on Bayesian learning approach was used as a prediction model. The model was applied to four unimpaired stream gages in Utah that spatially covers the state from north to south. Different models were developed based on the combinations of oscillation indices in the input. A total of 60 years (1950-2009) of data were used for the analysis. The model was trained on 50 years of data (1950-1999) and tested on 10 years of data (2000-2009). The best combination of oscillation indices and the lead-time were identified for each gage which was used to develop the prediction model. The predicted flow had reasonable agreement with the actual annual flow volume. The sensitivity analysis shows that the PDO and ENSO have relatively stronger effect compared to other oscillation indices in Utah. The prediction results from the MVRVM were compared with the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) where MVRVM performed relatively better.
