Sarla Pareek

Ordering policy for deteriorating items in a two-warehouse environment with partial backlogging

In the present study, we consider the two-warehouse inventory problem for deteriorating items with constant demand rate. Shortages are allowed and partially backlogged. A rented warehouse (RW) is used to store the excess units over the fixed capacity of the own warehouse (OW). According to first-in-first-out (FIFO) policy, the items that are stored first are used first. FIFO policy yields fresh and good conditioned stock thereby resulting in customer satisfaction, especially when items are deteriorating in nature. However, usually the two warehousing systems assume that the holding cost of items is more in RW than the OW due to modern preserving facilities. Thus, to reduce the inventory costs, it is imperative to consume the goods of RW at the earliest time. This approach is termed as last-in-first-out (LIFO) approach. The objective of the present research is to extend a two-warehouse inventory model with FIFO and LIFO dispatching policies with partial

A Warehouse Imperfect Fuzzified Production Model with Shortages under Inflationary Conditions

We develop a two-warehouse production model with imperfect items. Production rate is taken as the linear combination of on-hand inventory and demand, while demand rate is taken as function of time. Most of the researchers consider that the production rate is independent from the demand rate. In this paper we assume production rate as being dependent on the demand rate, and this assumption is more realistic. Shortages are allowed and partially backlogged with time-dependent backlogging rate. Due to different preservation facilities we consider that the deterioration rate is time dependent in own warehouse (OW) and Weibull distribution deterioration in rented warehouse (RW). Holding cost in RW is greater than in OW. We developed a fuzzy model with fuzzifying all the costs of the model as triangular fuzzy numbers. The present model is developed in both crisp and fuzzy senses. Finally, numerical example is shown, and sensitivity is also illustrated.

Loss Profit Estimation Using Temporal Association Rule Mining

Temporal association rule mining is a data mining technique in which relationships between items which satisfy certain timing constraints can be discovered. This paper presents the concept of temporal association rules in order to solve the problem of classification of inventories by including time expressions into association rules. Firstly, loss profit of frequent items is calculated by using temporal association rule mining algorithm. Then, the frequent items in particular time-periods are ranked according to descending order of loss profits. The manager can easily recognize most profitable items with the help of ranking found in the paper. An example is illustrated to validate the results. KEywoRdS ABC Classification, Data Mining, Inventory Management, Loss Profit, Temporal Association Rule Mining

Ordering Policy in a Two-Warehouse Environment for Deteriorating Items with Shortages under Inflationary Conditions

In this paper, the two-warehouse inventory problem is considered for deteriorating items with constant demand rate and shortages under inflationary conditions. In todays unstable global economy, the effects of inflation and time value of money cannot be ignored; as it increases the cost of goods. To safeguard from the rising prices, during the inflation regime, the organization 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. Further ahead, in the real business world, to retain the freshness of the commodity, most of the organizations adopt the first-in-first-out FIFO dispatching policy. FIFO policy yields fresh and good conditioned stock thereby resulting in customer satisfaction, especially when items are deteriorating in nature. However, the two warehousing systems usually assume that the holding cost of items is more in RW than the OW due to modern preserving techniques. Therefore, to reduce the inventory costs, it is economical to consume the goods of RW at the earliest. This approach is termed as Last-In-First-Out LIFO approach. The objective of the present research is to develop a two warehouse inventory model with FIFO and LIFO dispatching policies under inflationary conditions. Further, comparison between FIFO and LIFO policies has been exhibited with the help of a numerical example. Sensitivity analysis has also been performed to study the impact of various parameters on the optimal solution.

Fuzzy EOQ models for deterioration items under discounted cash flow approach when supplier credits are linked to order quantity

The article deals with a fuzzy inventory model for deteriorating items under a situation in which a supplier offers the purchaser some credit, proportional to the ordered quantity by purchaser. Shortages are not allowed. The effects of the inflation rate on the purchase price, ordering price and holding price, deterioration of units and permissible delay in payments are discussed in this article. A mathematical formulation is developed when inventory units are subject to fuzzy deterioration under inflation when the supplier offers a permissible delay to the purchaser if the order quantity is greater than or equal to a quantity which is specified. An optimal solution is obtained and algorithm is also given for finding the optimal order quantity and replenishment time, which gives the minimisation of the total cost of an inventory system in four different cases. The article concluded with a numerical example to illustrate the theoretical results where interdependence of parameter is studied for the optimal solution.

Regression Analysis of Collinear Data using r-k Class Estimator: Socio-Economic and Demographic Factors Affecting the Total Fertility Rate (TFR) in India

A basic assumption concerned with general linear regression model is that there is no correlation (or no multicollinearity) between the explanatory variables. When this assumption is not satisfied, the least squares estimators have large variances and become unstable and may have a wrong sign. Therefore, we resort to biased regression methods, which stabilize the parameter estimates. Ridge regression (RR) and principal component regression (PCR) are two of the most popular biased regression methods which can be used in case of multicollinearity. But the r-k class estimator, which is composed by combining the RR estimator and the PCR estimator into a single estimator gives the better estimates of the regression coefficients than the RR estimator and PCR estimator.This paper explores the multiple regression technique using r-k class estimator between TFR and other socio-economic and demographic variables and the data has been taken from the National Family Health Survey-III (NFHS-III): 29 states of India. The analysis shows that use of contraceptive devices shares the greatest impact on fertility rate followed by maternal care, use of improved water, female age at marriage and spacing between births.

Cooperative/Non-cooperative Supply Chain Models for Imperfect Quality Items with Trade Credit Financing

This paper studies the cooperative and non-cooperative models between the two partners of the supply chain system, seller and buyer. In this paper, supply chain models are formulated for imperfect quality items in which end demand of the product depends upon the retail price. The fixed credit period is offered by the seller to the buyer to stimulate his sales. The inspection process is also applied to each supplied lot at buyer’s end, and all the inspected items are separated into perfect quality items and imperfect quality items. Once the inspection process completed, perfect quality items are sold at selling price and imperfect quality items are sold at rebated/discounted price. The selling price and credit period proposed by the seller are considered as decision variables. The lot size and retailer price are decision variables of the buyer. In the proposed model, optimal policies of the seller’s and buyer’s are obtained under cooperative and non-cooperative analogue which will enhance the supply chain profit. Cooperative relationship is derived by a Pareto-efficient solution method, and non-cooperative is obtained by Seller-Stackelberg approach. Finally, numerical illustrations with sensibility analysis are stated to exemplify the theory of the paper.

Effects of imperfect quality items in the asymmetric information structure in supply chain model

Article history: Received March 2, 2017 Received in revised format October 10, 2017 Accepted November 3 2017 Available online November 3 2017 Most of the supply chain models have been developed under symmetric information structure i.e. players have complete knowledge of each other’s policies. But in most of the cases, players do not have complete information about the other players i.e. some information regarding their businesses is hidden. This paper studies supply chain model of imperfect quality items under asymmetric information in which unit price taken by the buyer and unit marketing expenditure are influencing product’s demand. This information is hidden to seller. The seller delivers the supply to the buyer. Each delivered lot goes through an inspection process at the buyer’s side. In the inspection process, the items are divided into two categories. The first category is perfect quality items while the second category is of imperfect quality items. After the inspecting the lots, the perfect quality commodities are to be sold at selling price and the imperfect items are supposed to get sold at a discounted price. The interaction between two constituents of the supply chain is modeled by non-cooperative Seller Stackelberg game approach in which the role of leader is played by the seller while the role of follower is played by the buyer. In our proposed model, the seller does not have information related to market demand but the buyer does. Numerical examples and sensitivity analysis explain the significance of the theory. Growing Science Ltd. All rights reserved. 8

Supply chain models with imperfect quality items when end demand is sensitive to price and marketing expenditure

This paper studies supply chain model for imperfect quality items under which unit price and unit marketing expenditure imposed by the buyer, regulates the demand of the item. It is presumed that with the accustomed supply chain model, all produced items are of good quality, coincidentally, it engrosses some percentage of defective items. Thus, inspection process becomes essential for the buyer to segregate the defective items, which are then sold at discounted price at the end of the screening process. In this paper, a supply chain model is ensued to substantiate the interaction and democracy of the participants in the supply chain, the buyer and seller, is pitched by non-cooperative and cooperative game theoretical approaches. In the non-cooperative method, the Stackelberg game approach is used in which one player behaves as a leader and another one as a follower. The co-operative game approach is based on a Pareto efficient solution concept, in which both the players work together to enhance their profit. Lastly, to demonstrate the significance of the theory of the paper, numerical examples including sensitivity analysis are presented.

An integrated inventory model involving discrete setup cost reduction, variable safety factor, selling-price dependent demand, and investment

This paper develops a sustainable integrated inventory model for maximizing profit with a controllable lead time, discrete setup cost reduction, and consideration of environmental issues. Contrary to the available literature, this paper considers a discrete setup cost for the vendor, thus making the integrated model sustainable. The customer’s demand is assumed to be selling-price dependent to increase the number of sales, and the lead time demand follows a Poisson distribution. The integrated model is used to optimized the total shipment number, volume of shipments, safety factor, investments, selling-price, and probability of moving between the “in-control” to “out-of-control” states. An algorithm is developed to obtain the numerical results. Numerical examples and sensitivity analyses are given to illustrate the model.