Learning curves monitor the performance of workers for the given new task as well as it is a mathematical representation of the same learning process which can be analyzed after frequent repetitions. Now-a-days learning curve is a promotion effective tool for management concern with designing and controlling the process of imperfect production and redesigning unbalanced business operations in the production of goods or services related to scheduling, uncontrolled inventory management, quality management as well as inspection. Learning effect has direct impact in calculation of profit or loss. Generally, a business seller, in order to increase his sale prefers to lend his products to buyers for a definite period of time. There is no penalty before or during this definite time period however after the duration of lending time period is over, he will assign some extra charges. For this action, seller offers a trade credit financing period to his buyer. Assuming when buyer receives a lot he separates the defective and non-defective items by a screening process and defective items are then sold at a discounted price. The percentage of defective items decreases per lot according to learning curve. Seller too plans which condition is beneficial for good coordination of retailers and analysts. Different cases are explained broadly in this model to get maximum profit. In this paper, a fiscal construction feature model for imperfect quality items with trade credit policy is analyzed under the effects of learning. Total profit function per cycle has been derived with the help of involvement of different costs and related parameters for the retailers and a numerical example given ahead shows the verification of results. The impacts of key parameters of the model are studied by sensitivity analysts to deduce managerial insights.

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.

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 article, a production inventory model is developed to determine the retailer’s optimal replenishment decisions under two levels of trade credit and limited storage space. Two levels of trade credit refers that the supplier provides to his/her retailer a permissible delay period to settle the account and the retailer also in turn provides a delay period to his/her customer for paying of purchasing goods. The retailer’s credit period M offered by supplier is greater than customers credit period N provides by the retailer. This paper investigates retailer optimal replenishment policy under finite replenishment rate by minimizing the total annual inventory cost. Three theorems are developed to determine optimal cycle time, optimal relevant cost and optimal order quantity for retailers accurate and rapidly. A numerical example is used to analyze the validity of propose model, Sensitive analysis shows managerial decisions for retailer.

In this paper, a multi products single machine economic production quantity model with
discrete delivery is developed. A unique cycle length is considered for all produced items with
an assumption that all products are manufactured on a single machine with a limited capacity.
The proposed model considers different items such as production, setup, holding, and
transportation costs. The resulted model is formulated as a mixed integer nonlinear
programming model. Harmony search algorithm, extended cutting plane and particle swarm
optimization methods are used to solve the proposed model. Two numerical examples are used
to analyze and to evaluate the performance of the proposed model.