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This study presents an inventory management framework that integrates preservation technology investments with demand influenced by price and advertisement frequency, while also examining the impact of carbon tax policies. Two models are considered: (i) a baseline model without carbon policies and (ii) an advanced model incorporating carbon tax policies to mitigate environmental impacts. The analysis explores the interplay between preservation technology investments and carbon emissions, providing insights into optimal pricing and replenishment strategies for managing deteriorating inventory with varying initial reference prices. The results highlight the effectiveness of preservation technologies in reducing deterioration rates, stabilizing costs and enhancing inventory quality. To operationalize these strategies, a practical iterative algorithm is developed, and validated through detailed numerical examples and key parameter analyses.

This paper focuses on imperfect manufacturing system with remanufacturing, manufacturing and product returned cycle for a single item which deteriorates with respect to time. The product has maximum fixed lifetime. To decrease deterioration of the product, manufacturer spends capitals on preservation technology to preserve the item. In this paper, the effect of inflation is also considered. Here, time-dependent quadratic demand is debated which is suitable for the products whose demand increases initially and afterward it starts to decrease. The objective is to minimize the total cost of manufacturer with respect to cycle time and investment for preservation technology. The model is supported with numerical example. Sensitivity analysis is done to derive insights for decision makers. Graphical result, in three dimensions, is exhibited with supervisory decision.

An integrated three-layer supply chain model for production and by-production system is formulated under fuzzy-rough (Fu-Ro)-environment. At first, supplier receives the deteriorating items in a lot and supplies the fresh units to manufacturer for production. Manufacturer has two plants: plant-1 and plant-2. Manufacturer purchases these fresh raw materials at a constant rate from supplier to produce the main product in plant-1. Retailer-I has purchased this product from manufacturer of plant-1 to sale to the customers. The residue units of plant-1 have transferred to plant-2 with constant rate to manufacture another usable by-product. Retailer-II purchases this usable by-product and sales to the customers. Ideal costs of supplier, manufacturer and retailer have been taken into account. By-production of residue units of plant-1 not only minimizes the environmental pollution, but also gives some return to the manufacturer. Due to the complexity of environment, inventory holding costs, idle costs and setup costs are considered as Fu-Ro type and these are reduced to crisp ones using Fu-Ro expectation. Supply rate, production and by-production rates are assumed as decision variables. Integrated model has been developed and solved analytically in crisp and Fu-Ro environments to find the optimum value of the decision variables and corresponding individual profits of the members of the supply chain are calculated numerically and graphically. Finally, the model has been realized with a case study of sugar mill.

The proposed EOQ model is a genuine attempt to manage retailer’s inventory when retailer’s stock is comprised of defective as well as constantly deteriorating items. Defective items in inventory are managed by selling them at discounted rate after a quality check process. Deterioration of items is controlled by investing suitable amount in preservation technology. The study assumes price sensitive quadratic demand incorporating the effect of inflation leading to a realistic situation. The objective of this paper is to maximize the retailer’s total profit with respect to cycle time, selling price, and preservation technology investment. Numerical examples are given to validate the model, and sensitivity analysis of inventory parameters is done to understand their effect. The outcome of this paper is applicable to goods like utility vehicles, stationary items, Fashion accessories, Cloths, Footwears, etc.

Inventory models are quite important when it comes to analyzing scenarios that occur in a variety of areas, including food, warehouses, vegetable markets, and other similar places. Within the scope of this study, we investigate both a linear and a nonlinear time-dependent inventory control model for things that are deteriorating. When it comes to conducting business in the modern day, the relationship that exists between retailers and customers is absolutely necessary for successful implementation. Consumers engage in commercial transactions with retailers in order to buy goods with the intention of increasing their earnings. The goal of this study is to calculate the number of times demand orders are placed by customers throughout the rotation time in order to achieve the highest possible overall profit for both the client and the merchant, both with and without the use of collaboration. In addition, it intends to investigate the disparity between the total profit obtained by the customer and the merchant in two different scenarios. Using analytical methods, the proposed model is evaluated in order to obtain the best possible solution to the problem. In the following section, a numerical example and a comparison study are discussed. Ultimately, a sensitivity analysis of the parameters is to be done to investigate the variations in the results of various parameters inside the model based on the optimal strategy.

This paper presents a sophisticated modification of the economic production quantity (EPQ) model. It incorporates Weibull-distributed progressive deterioration, dynamic holding costs, variable demand, and strong strategies for effectively handling shortages and backlogs. Targeting products that have a short-term expiration but can still be stored for a long time without significant deterioration, the model aims to increase production quantities while lowering overall variable expenses. The extended EPQ model utilizes Maclaurin series approximations to solve ordinary differential equations, effectively capturing the dynamics of inventory under three different demand patterns. The focus of this handle’s situations when the demand for a product changes in a predictable manner over time and considers the likelihood of defective goods during the manufacturing process. This approach provides useful insights for optimizing inventory management and production planning in the manufacturing of goods that are used up or consumed. The usefulness of the model is confirmed in the study through the use of two illustrative instances. Additionally, sensitivity analysis is utilized to suggest potential areas for additional investigation.