To balance inventory cost with diverse demand,an optimal investment decision on necessary process improvement for delayed product differentiation is studied. A two-stage flexible manufacturing system is modeled as a c...To balance inventory cost with diverse demand,an optimal investment decision on necessary process improvement for delayed product differentiation is studied. A two-stage flexible manufacturing system is modeled as a continuous time Markov chain. The first production stage manufactures semifinished products based on a make-to-stock policy. The second production stage customizes semi-finished products from the first production stage on a make-to-order policy. Various performance measures for this flexible manufacturing system are evaluated by using matrix geometric methods. An optimization model to determine the level of investment on process improvement that minimizes the manufacturer ’s total cost is established. The results show that,a higher investment level can reduce both the expected customer order fulfillment delay and the expected semi-finished products inventory. When the initial order penetration point is 0. 4,the manufacturer ’s total cost is reduced by 15. 89% through process investment. In addition, the optimal investment level increases with the increase in the unit time cost of customer order fulfillment delay,and decreases with the increase in the product value and the initial order penetration point.展开更多
The unforeseen mobile data explosion as well as the scarce of spectrum resource pose a major challenge to the performance of today＇s cellular networks which are in urgent need of novel solutions to handle such volumi...The unforeseen mobile data explosion as well as the scarce of spectrum resource pose a major challenge to the performance of today＇s cellular networks which are in urgent need of novel solutions to handle such voluminous mobile data. Long term evolution-unlicensed （LTE-U）, which extends the LTE standard operating on the unlicensed band, has been proposed to improve system throughput. In LTE-U system, arriving users will contend the unlicensed spectrum resource with wireless fidelity （WiFi） users to transmit data information. Nevertheless, there is no clear consensus as to the benefits of transmission using unlicensed bands for LTE users. To this end, in this paper an analytical model is presented based on a queue system to understand the performance achieved by unlicensed based LTE system taking quality of services （QoS） and LTE-U users＇ behaviors into account. To obtain the stead-state solutions of the queue system, a matrix geometric method is used to solve it. Then, the average delay and utilization of unlicensed band for the LTE-U users is derived by using the queuing model. The performance of LTE-U coexistence is evaluated with WiFi using the proposed model and provide some initial insights as to the advantage of LTE-U in practice.展开更多
In this paper,we consider a GI/M/1 queue operating in a multi-phase service environment with working vacations and Bernoulli vacation interruption.Whenever the queue becomes empty,the server begins a working vacation ...In this paper,we consider a GI/M/1 queue operating in a multi-phase service environment with working vacations and Bernoulli vacation interruption.Whenever the queue becomes empty,the server begins a working vacation of random length,causing the system to move to vacation phase 0.During phase 0,the server takes service for the customers at a lower rate rather than stopping completely.When a vacation ends,if the queue is non-empty,the system switches from the phase 0 to some normal service phase i with probability qi,i=1,2,⋯,N.Moreover,we assume Bernoulli vacation interruption can happen.At a service completion instant,if there are customers in a working vacation period,vacation interruption happens with probability p,then the system switches from the phase 0 to some normal service phase i with probability qi,i=1,2,⋯,N,or the server continues the vacation with probability 1−p.Using the matrix geometric solution method,we obtain the stationary distributions for queue length at both arrival epochs and arbitrary epochs.The waiting time of an arbitrary customer is also derived.Finally,several numerical examples are presented.展开更多
基金The National Natural Science Foundation of China(No.71661147004)
文摘To balance inventory cost with diverse demand,an optimal investment decision on necessary process improvement for delayed product differentiation is studied. A two-stage flexible manufacturing system is modeled as a continuous time Markov chain. The first production stage manufactures semifinished products based on a make-to-stock policy. The second production stage customizes semi-finished products from the first production stage on a make-to-order policy. Various performance measures for this flexible manufacturing system are evaluated by using matrix geometric methods. An optimization model to determine the level of investment on process improvement that minimizes the manufacturer ’s total cost is established. The results show that,a higher investment level can reduce both the expected customer order fulfillment delay and the expected semi-finished products inventory. When the initial order penetration point is 0. 4,the manufacturer ’s total cost is reduced by 15. 89% through process investment. In addition, the optimal investment level increases with the increase in the unit time cost of customer order fulfillment delay,and decreases with the increase in the product value and the initial order penetration point.
基金supported by Beijing Municipal Commission of Education (201501001)Beijing Municipal Science and Technology Commission (Z16111000500000)+1 种基金the National Natural Science Foundation of China (61671073)supported by Beijing Laboratory of Advanced Information Network
文摘The unforeseen mobile data explosion as well as the scarce of spectrum resource pose a major challenge to the performance of today＇s cellular networks which are in urgent need of novel solutions to handle such voluminous mobile data. Long term evolution-unlicensed （LTE-U）, which extends the LTE standard operating on the unlicensed band, has been proposed to improve system throughput. In LTE-U system, arriving users will contend the unlicensed spectrum resource with wireless fidelity （WiFi） users to transmit data information. Nevertheless, there is no clear consensus as to the benefits of transmission using unlicensed bands for LTE users. To this end, in this paper an analytical model is presented based on a queue system to understand the performance achieved by unlicensed based LTE system taking quality of services （QoS） and LTE-U users＇ behaviors into account. To obtain the stead-state solutions of the queue system, a matrix geometric method is used to solve it. Then, the average delay and utilization of unlicensed band for the LTE-U users is derived by using the queuing model. The performance of LTE-U coexistence is evaluated with WiFi using the proposed model and provide some initial insights as to the advantage of LTE-U in practice.
基金the National Natural Science Foundation of China(No.61773014)。
文摘In this paper,we consider a GI/M/1 queue operating in a multi-phase service environment with working vacations and Bernoulli vacation interruption.Whenever the queue becomes empty,the server begins a working vacation of random length,causing the system to move to vacation phase 0.During phase 0,the server takes service for the customers at a lower rate rather than stopping completely.When a vacation ends,if the queue is non-empty,the system switches from the phase 0 to some normal service phase i with probability qi,i=1,2,⋯,N.Moreover,we assume Bernoulli vacation interruption can happen.At a service completion instant,if there are customers in a working vacation period,vacation interruption happens with probability p,then the system switches from the phase 0 to some normal service phase i with probability qi,i=1,2,⋯,N,or the server continues the vacation with probability 1−p.Using the matrix geometric solution method,we obtain the stationary distributions for queue length at both arrival epochs and arbitrary epochs.The waiting time of an arbitrary customer is also derived.Finally,several numerical examples are presented.
