Keeping in view the concern about environmental protection, the study investigates effects of remanufacturing in an integrated production inventory model consisting of forward and reverse supply chain over infinite planning horizon. This article is developed for the deteriorating products with stock dependent demand under shortages. To make the model more realistic, flexibility of production system has been incorporated during forward manufacturing. We derive total cost function and using the results of calculus, optimum production policy is derived, which minimizes the total cost incurred. The results are discussed with a numerical example to illustrate the theory.

In this paper, an inventory model of two-warehouse is considered, which evaluates the impact of a reduction rate in the selling price with volume flexibility. In real life, there are many products, which may decay or deteriorate or become obsolete. Therefore, one alternative is to clear the stock by selling a large amount of items at reduced prices. Taking this concept into account, this paper considers a fixed demand rate at the beginning of planning until the certain time point occurs, while demand is assumed to follow the pattern of nonlinear and non-decreasing power function of the reduction rate. The total cost function includes warehouse and rented warehouse holding costs, set up cost and the production cost. Numerical illustrations are given to exemplify the model and the proposed model is solved using a Genetic Algorithm (GA) with sensitivity analysis.

This study develops an integrated production inventory model from the perspectives of vendor, supplier and buyer. The demand rate is time dependent for the vendor and supplier and buyer assumes the stock dependent demand rate. As per the demand, supplier uses two warehouses (rented and owned) for the storage of excess quantities. Shortages are allowed at the buyer’s part only and the unfulfilled demand is partially backlogged. The effect of imperfect production processes on lot sizing is also considered. This complete model is studied under the effect of inflation. The objective is to minimize the total cost for the system. A solution procedure is developed to find a near optimal solution for the model. A numerical example along with sensitivity analysis is given to illustrate the model.

In this paper, a supply chain inventory model is developed in inflationary environment by incorporating some realistic features such as ramp type demand, deterioration, partial backlogging, inflation, and trade credit. Here, rate of deterioration is linear and partial backlogging rate is variable and dependent on the waiting time for the next replenishment. Depending on the trade credit period, three different situations arise. For each model the optimal replenishment policy is determined. Numerical examples are provided to illustrate the proposed inventory model and sensitivity analyses of optimal solutions are given for each case of trapezoidal demand function.

In this study, a volume flexible inventory system for deteriorating items with stock & time dependent demand has been developed over a finite planning horizon. Shortages are permitted with partial backorder. Uncertainties are inherent in real inventory problems due to complexities of market situation. This uncertainty can be handled by the concept of randomness. As a result, backorder rate is taken as random and follows a probability distribution. All the costs are influenced by the learning effect. The optimal number of production cycles that minimize the total cost is considered. Numerical illustrations together with sensitivity analysis are given to elucidate the model. Furthermore, the numerical results of the finite planning horizon model have been plotted graphically.

The concept of green inventory systems is very important for economic growth and development in the era of sustainable development. There is a special need for green inventory systems to identify and manage perishable products since spoilage and deterioration can lead to significant losses of items, which negatively affect the satisfaction of consumers. As perishable products decay continuously (such as vegetables, fruits, milk, juices, frozen foods, baked foods), their demand is adversely affected as well as customers' purchasing decisions. The more realistic assumption is a price-sensitive demand. As well as deterioration rates, perishable products have an expiration date-dependent deterioration rate. Further, inventory holding, and the deterioration of perishables contribute significantly to carbon emissions when operating the inventory system. A carbon tax policy is more flexible and effective when it comes to reducing carbon emissions due to its environmental conscious nature. We develop two sustainable inventory procedures for perishable items based on a practical scenario in which the buyer has a limited storeroom. So, to achieve sustainability goals, a model for inventory management for perishable products based on expiration dates is presented in this paper. We distinguish between two inventory schemes: (i) one that allows shortages and fractional backlogs, and (ii) one that does not allow shortage. In both schemes, both the decay rate and demand function show an upward trend against storage time. Since the decay rate increases with storage time, it is assumed that the cost of storing items is linearly related to storage time. numerical examples along with a real-life case study are presented to validate the inventory schemes after several decision-making findings have been derived.

For today’s high competitive market, when immensity purchasing of inventory becomes convenient or obligatory, to discover an alternative market in order to maximize the revenue earned is a tradition. In this paper, we considered an inventory model for seasonal products with Weibull rate of deterioration having two potential markets, say, primary and alternate. To handle the inventory up to the next season will result an increase in total cost. So it is a favorable task to transfer the remaining stock to the alternate market even at a slightly differ in selling price. Solution procedure, numerical examples and sensitivity analysis for different variables are presented to illustrate the model.