The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
K S Chaudhuri - One of the best experts on this subject based on the ideXlab platform.
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an eoq model for deteriorating items with a Linear Trend in demand and shortages in all cycles
International Journal of Production Economics, 1997Co-Authors: T Chakrabarti, K S ChaudhuriAbstract:Abstract We consider here the inventory replenishment problem over a finite time horizon for a deteriorating item with a Linear Trend in demand, equal replenishment cycles and shortage in every cycle. The reorder number, the interval between two successive reorders and the shortage intervals are all determined in an optimal manner so as to minimize the average system cost. The advantage of allowing shortage in all cycles is illustrated with a numerical example.
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an eoq model for deteriorating items with shortages and a Linear Trend in demand
Journal of the Operational Research Society, 1991Co-Authors: Adrijit Goswami, K S ChaudhuriAbstract:We consider here the inventory replenishment policy over a fixed planning period for a deteriorating item having a deterministic demand pattern with a Linear Trend and shortages. The number of reorders, the interval between two successive reorders and the shortage intervals over a finite time-horizon are all determined in an optimal manner so as to keep the average system cost to a minimum. One numerical example illustrates how the procedure works. The counterpart of this example in the no-shortage case is also given. The effects of variation in the deterioration rate on the optimal policy are also indicated with numerical examples.
Priyanka Verma - One of the best experts on this subject based on the ideXlab platform.
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two warehouse partial backlogging inventory model for deteriorating items with Linear Trend in demand under inflationary conditions
International Journal of Systems Science, 2011Co-Authors: Chandra K Jaggi, Aditi Khanna, Priyanka VermaAbstract:In today's business transactions, there are various reasons, namely, bulk purchase discounts, re-ordering costs, seasonality of products, inflation induced demand, etc., which force the buyer to order more than the warehouse capacity. Such situations call for additional storage space to store the excess units purchased. This additional storage space is typically a rented warehouse. Inflation plays a very interesting and significant role here: It increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space, which is facilitated by a rented warehouse. Ignoring the effects of the time value of money and inflation might yield misleading results. In this study, a two-warehouse inventory model with Linear Trend in demand under inflationary conditions having different rates of deterioration has been developed. Shortages at the owned warehouse are also allowed subject to partial backlogging. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. Finally, findings have been illustrated with the help of numerical examples. Comprehensive sensitivity analysis has also been provided.
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two warehouse inventory model for deteriorating items with Linear Trend in demand and shortages under inflationary conditions
International Journal of Procurement Management, 2010Co-Authors: Chandra K Jaggi, Priyanka VermaAbstract:Inflation plays a very interesting and significant role: it increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space that is facilitated by a rented warehouse. Ignoring the effects of time value of money and inflation might yield misleading results. In the present study, a 'two-warehouse inventory model with Linear Trend in demand under the inflationary conditions' has been developed. A rented warehouse (RW) is used to store the excess units over the capacity of the own warehouse (OW). The stock is being transferred from rented warehouse to own warehouse in a continuous release pattern with per unit transportation cost being factored in. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. The results have been elucidated with numerical examples.
Zeyu Zheng - One of the best experts on this subject based on the ideXlab platform.
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WSC - Estimation and Inference for Non-Stationary Arrival Models with a Linear Trend
2019 Winter Simulation Conference (WSC), 2019Co-Authors: Peter W. Glynn, Zeyu ZhengAbstract:This paper is concerned with building statistical models for non-stationary input processes with a Linear Trend. Under a Poisson assumption, we investigate the use of the maximum likelihood (ML) method to estimate the model and establish limiting behavior for the ML estimator in an asymptotic regime that naturally arises in applications with high-volume inputs. We also develop likelihood ratio tests for the presence of a Linear Trend and discuss the asymptotic efficiency. Change-point detection procedures are discussed to identify an unknown point when the model switches from a stationary mode to non-stationarity with a Linear Trend. Numerical experiments on an e-commerce data set are included. Incorporating a Linear Trend into an input model can improve prediction accuracy and potentially enhance associated performance evaluations and decision making.
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Estimation and Inference for Non-Stationary Arrival Models with a Linear Trend
2019 Winter Simulation Conference (WSC), 2019Co-Authors: Peter W. Glynn, Zeyu ZhengAbstract:This paper is concerned with building statistical models for non-stationary input processes with a Linear Trend. Under a Poisson assumption, we investigate the use of the maximum likelihood (ML) method to estimate the model and establish limiting behavior for the ML estimator in an asymptotic regime that naturally arises in applications with high-volume inputs. We also develop likelihood ratio tests for the presence of a Linear Trend and discuss the asymptotic efficiency. Change-point detection procedures are discussed to identify an unknown point when the model switches from a stationary mode to non-stationarity with a Linear Trend. Numerical experiments on an e-commerce data set are included. Incorporating a Linear Trend into an input model can improve prediction accuracy and potentially enhance associated performance evaluations and decision making.
Chandra K Jaggi - One of the best experts on this subject based on the ideXlab platform.
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two warehouse partial backlogging inventory model for deteriorating items with Linear Trend in demand under inflationary conditions
International Journal of Systems Science, 2011Co-Authors: Chandra K Jaggi, Aditi Khanna, Priyanka VermaAbstract:In today's business transactions, there are various reasons, namely, bulk purchase discounts, re-ordering costs, seasonality of products, inflation induced demand, etc., which force the buyer to order more than the warehouse capacity. Such situations call for additional storage space to store the excess units purchased. This additional storage space is typically a rented warehouse. Inflation plays a very interesting and significant role here: It increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space, which is facilitated by a rented warehouse. Ignoring the effects of the time value of money and inflation might yield misleading results. In this study, a two-warehouse inventory model with Linear Trend in demand under inflationary conditions having different rates of deterioration has been developed. Shortages at the owned warehouse are also allowed subject to partial backlogging. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. Finally, findings have been illustrated with the help of numerical examples. Comprehensive sensitivity analysis has also been provided.
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two warehouse inventory model for deteriorating items with Linear Trend in demand and shortages under inflationary conditions
International Journal of Procurement Management, 2010Co-Authors: Chandra K Jaggi, Priyanka VermaAbstract:Inflation plays a very interesting and significant role: it increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organisation prefers to keep a higher inventory, thereby increasing the aggregate demand. This additional inventory needs additional storage space that is facilitated by a rented warehouse. Ignoring the effects of time value of money and inflation might yield misleading results. In the present study, a 'two-warehouse inventory model with Linear Trend in demand under the inflationary conditions' has been developed. A rented warehouse (RW) is used to store the excess units over the capacity of the own warehouse (OW). The stock is being transferred from rented warehouse to own warehouse in a continuous release pattern with per unit transportation cost being factored in. The solution methodology provided in the model helps to decide on the feasibility of renting a warehouse. The results have been elucidated with numerical examples.
Chenghsing Hung - One of the best experts on this subject based on the ideXlab platform.
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an inventory model for deteriorating items with Linear Trend demand under the condition of permissible delay in payments
Production Planning & Control, 2001Co-Authors: Horngjinh Chang, Chenghsing HungAbstract:In this article, we consider the inventory replenishment problem with varying rate of deterioration and condition of permissible delay in payments, in which the restrictive assumption of constant demand rate is relaxed, and take a Linear Trend in demand into consideration. An algorithm is developed to determine the optimal replenishment cycle. We also provide a special case to illustrate the proposed model. Finally, a numerical example is presented to illustrate the optimization procedure. Sensitivity analysis of the parameter value is also carried out.
