In most of the published articles dealing with optimal order quantity model under permissible delay in payments, it is assumed that the supplier only put forwards fully permissible delay in payments if retailer ordered a bulky sufficient quantity otherwise permissible delay in payments would not be permitted. Practically, in competitive market environments and recession phases of business, every supplier wants to attract more retailers by the help of providing good facilities for trading. Necessity of order quantity may put a negative pressure on supplier’s demand. So, within the economic order quantity (EOQ) framework the main purpose of this paper is to broaden this extreme case by introducing a new credit policy, Flexible Trade Credit Policy (FTCP), for supplier which can help him provide more free space of trading to retailers. This policy, after adopting by suppliers, not only provides attractive trading environments for retailers but also enhances the demand of supplier due to the large number of new retailers. Here in, under this policy, an inventory system is investigated as a cost minimization problem to establish the retailer’s optimal inventory cycle time and optimal order quantity. Three theorems are established to describe and to lighten optimal replenishment policies for the retailer. Finally, numerical examples are considered to illustrate all these theorems and managerial insights are given based on considered numerical examples.

The overall objective of this paper is to present a comprehensive comparison between the EOQ model and JIT system to see either of them under which circumstances is more cost effective. There have been a few researchers dealing with the EOQ/JIT comparison model to guide companies whether or not switch to JIT or EOQ, however, their proposed models could be more realistic by taking some effective factors, such as hidden costs of a JIT system, interest rate, inflation rate, etc., into account. This research, by considering some less seen costs of both EOQ model and JIT system, develops the previous proposals of the EOQ/JIT model. This paper analyzes the impact of increasing or decreasing some determinant factors such as the interest rate, from cost perspective, to help the decision on whether or not to switch the inventory system, however, to make such a decision, companies may also take some other factors into account. A sensible link is created between the EOQ/JIT model and financial management to assure the decision makers that their financial concerns are observed in this model.

Hsu and Hsu (2013a) established a closed-form solution for an EOQ model with imperfect quality items, inspection errors, shortage backordering, and sales returns, where the customers who return the defective items will receive full price refunds; i.e., the returned items are not replaced with good items. In this note, we extend Hsu and Hsu & apos; s (2013a) work to consider the case that returned items are replaced with good items. A closed-form solution is developed for the optimal order size and the maximum shortage level. Numerical examples are provided to show the differences in the optimal solutions when returned items are replaced, and when they are not.

Inventories are the materials stored either waiting for processing or experiencing processing and in some cases for future delivery. Inventories are treated both as blessings and evil. As they are like money placed in a drawer, assets tied up in investments, incurring costs for the care of the stored material and also subject to spoilage and obsolescence there have been a spate of programs developed by industries, all aimed at reducing inventory levels and increasing efficiency on the shop floor. Nevertheless, they do have positive purposes such as stable source of input required for production, less replenishment and may reduce ordering costs because of economies of scale. Finished goods inventories provide for better customer service. So formulating a suitable inventory model is one of the major concerns for an industry. Again considering reliability of any process is an important trend in the current research activities. Inventory models could be both deterministic and probabilistic and both of which must account for the reliability of the associated production process. This paper discusses the major works in the field of inventory modeling driven by reliability considerations, which ranges from the very beginning to latest works just published.

In this paper, we develop a two-warehouse imperfect production model under two cases: (i) model starts with shortages (ii) model ends with shortages. Most of the researchers proposed the models for perfect items but we develop for imperfect quality items, which is very realistic. Demand is taken as time dependent and dependent on the production. Holding cost in rented warehouse (RW) is greater than own warehouse (OW). Deterioration is taken as Weibull distribution in both OW and RW. Shortages are allowed and partially backlogged. The effect of learning on production cost is also considered. Learning from one cycle to other cycle, improve the efficiency of the organization. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

Timely identification of newly emerging trends is needed in business process. Data mining techniques like clustering, association rule mining, classification, etc. are very important for business support and decision making. This paper presents a method for redesigning the ordering policy by including cross-selling effect. Initially, association rules are mined on the transactional database and EOQ is estimated with revenue earned. Then, transactions are clustered to obtain homogeneous clusters and association rules are mined in each cluster to estimate EOQ with revenue earned for each cluster. Further, this paper compares ordering policy for imperfect quality items which is developed by applying rules derived from apriori algorithm viz. a) without clustering the transactions, and b) after clustering the transactions. A numerical example is illustrated to validate the results.

The purpose of these comments is to serve as a revision to the article by Khan, Jaber, & Bonney [2011, An economic order quantity (EOQ) for items with imperfect quality and inspection errors, International Journal of Production Economics, 133: 113–118]. This commenting paper first suggests that the revenue function derived in Khan et al. (2011) is unrealistic, and then offers revisions to complement the shortcomings.

In this paper, we develop an integrated vendor-buyer production-inventory model for items with imperfect quality and inspection errors. The production process is imperfect and produces a certain number of defective items with a known probability density function. We consider the policy in which the delivery quantity to the buyer is identical at each shipment. Once the buyer receives the lot, a 100% screening process of the lot is conducted, and the screening process and demand proceed simultaneously. The screening process is not perfect. The inspector may incorrectly classify a non-defective item as defective, or incorrectly classify a defective item as non-defective. The expected integrated total annual cost of the vendor and the buyer is derived and a solution procedure is provided to find the optimal solution. Numerical examples show that the integrated model gives an impressive cost reduction in comparison to an independent decision by the buyer.

Wee et al. (2007) developed an optimal inventory model. In this technical note, we point out a contradiction between Wee et al. & apos; s model and their assumption. A corrected model is developed based on their assumption. Numerical examples show that in terms of the two decision variables, there is a significant difference between the corrected model and Wee et al. & apos; s model. The results also show that that the penalty of using Wee et al. & apos; s model can be significant under certain situations.

This paper considers the economic order quantity (EOQ) model over a finite horizon, in which demand rate follows a two-parameter Weibull time-dependent, shortages are allowed and completely backlogged. Mathematical formulations are derived under two different circumstances i.e. case I: The permissible delay is less than or equal time to finish positive inventory for settling the account, and case II: The permissible delay period is greater than time to finish positive inventory for settling the account. Based on the optimal solutions some important results are derived and numerical examples are provided to validate the proposed model. Finally, sensitivity analysis is provided to analyze the effect of changes with the variation in one parameter at a time on the optimal solution.