An EOQ Model with Carbon Emissions and Inflation for Deteriorating Imperfect Quality Items under Learning Effect

In this paper, economic order quantity (EOQ) models without shortages for single item and multi-items are presented. Here, the holding cost of the item is a continuous function of the order quantity. The costs involved in this model are imprecise in nature. The main contributions of this research are as follows: The proposed EOQ model is discussed in two cases by describing the model in an uncertain environment. In case-1, EOQ models with fuzzy parameters (like ordering cost, holding cost, and unit product cost) are considered. Here all the fuzzy parameters are represented by trapezoidal fuzzy numbers. The said EOQ model is carried out by using the signed-distance method. In case-2, EOQ models with interval parameters (like ordering cost, holding cost, unit product cost, and the total money investment for the quantities) are considered. This proposed model is solved by using interval linear programming problem (ILPP) technique based on the best and the worst optimum values of the objective function. Numerical examples are given to exemplify the proposed model and also the results of different models are compared.KeywordsEOQTrapezoidal fuzzy numberInterval numberSigned-distance methodInterval linear programming problem (ILPP)

An economic order quantity model with reverse logistics program

Study of memory effect in an inventory model for deteriorating items with partial backlogging

An EOQ model with delay in payments and time varying deterioration rate

The classical economic order quantity (EOQ) model assumes that items produced are of perfect quality and that die unit cost of production is independent of demand. Product quality is not always perfect but directly affected by the reliability of the production process used to produce the products. In addition, a relationship between unit production cost and demand may exist under certain circumstances. We propose an EOQ model with demand-dependent unit production cost and imperfect production processes. We formulate this inventory decision problem as a geometric program (GP) and solve it to obtain closed-form optimal solutions. An illustrative example is provided to demonstrate the point that GP has potential as a valuable analytical tool for studying a certain class of inventory control problems. We also discuss the aspect of sensitivity analysis based on the GP approach.

Study’s Excerpt/Novelty This study introduces a novel economic order quantity (EOQ) model for managing non-instantaneous deteriorating items under two-phase demand rates and linear holding costs, incorporating constant partial backlogging and two-level pricing strategies within a trade credit framework. The model uniquely addresses the complexities of time-dependent quadratic demand before deterioration and constant demand afterward, providing optimal solutions for maximizing total profit by determining the best timing for positive inventory, cycle length, and order quantity. The research not only establishes the theoretical existence and uniqueness of these optimal solutions but also demonstrates practical implications through numerical examples and sensitivity analyses, highlighting the critical impact of deterioration rates on inventory management and profitability. Full Abstract This research developed an economic order quantity model for non-instantaneous deteriorating items with two-phase demand rates, linear holding cost, constant partial backlogging rate and two-level pricing strategies under trade credit policy. It is assumed that the holding cost is linear time-dependent, the unit selling price before deterioration sets in is greater than that after deterioration sets and the demand rate before deterioration sets in is considered as continuous time-dependent quadratic, after which it is considered as constant up to when the inventory is completely exhausted. Shortages are allowed and partially backlogged. The purpose of the model is to determine the optimal time with positive inventory, cycle length and order quantity such that the total profit of the inventory system has a maximum value. The necessary and sufficient conditions for the existence and uniqueness of the optimal solutions have been established. Some numerical examples have been given to illustrate the theoretical result of the model. Sensitivity analysis of some model parameters on the decision variables has been carried out and suggestions towards maximising the total profit were also given. , it is seen that the higher the rate of deterioration the lower the optimal time with positive inventory ( ), cycle length order quantity and the total profit and vice versa. This implies that the retailer needs to take all the necessary measures to avoid or reduce deterioration to maximise higher profit. Based on the results application of the model led to an increase in revenue.

Economic order quantity and sampling inspection plans for imperfect items

In this article, we extended Goyal's model to develop an Economic Order Quantity (EOQ) model in which the supplier offers the retailer the permissible delay period M, and the retailer in turn provides the trade credit period N (with N ≤ M) to his/her customers. In addition, we assume that (1) the retailer's selling price per unit is necessarily higher than its unit cost, and (2) the interest rate charged by a supplier or a bank is not necessarily higher than the retailer's investment return rate. We then establish an appropriate EOQ model with trade credit financing, and provide an easy-to-use closed-form solution to the problem. Furthermore, we find it is possible that a well-established buyer may order a lower quantity and take the benefit of the permissible delay more frequently, which contradicts to the result by the previous researchers. Finally, we perform some sensitivity analyses to illustrate the theoretical results and obtain some managerial results.

The effects of inflation and time-value of money on an economic order quantity model with a random product life cycle

This paper conducts an in-depth analysis of three models derived from economic order quantity (EOQ) model in an effort to reduce high inventory cost associated with the IT commodities sold in one of the Carrefour supermarket outlets. These three models are: 1. model of lots ordered and delivered independently, 2. model of lots ordered and delivered jointly, and 3. model of lots ordered and delivered for a selective subset. Mathematically, these three models are carefully discussed and compared in this paper. The third EOQ-based model contains more selective procedures combining the commodities to be ordered jointly in an order schedule and with that may lead to an optimal solution for its lowest cost.

Environmental sustainability EOQ model for closed-loop supply chain under market uncertainty: A case study of printer remanufacturing

This paper presents EOQ (Economic Order Quantity) model with stock- level dependent demand and different types of holding cost function. We show that the total relevant inventory cost per unit time is convex with respect to cycle time. Mathematical models are established to determine optimal order quantity and total relevant inventory cost. Numerical examples are provided for two different models i.e. (i): Instantaneous replenishment with inventory dependent holding cost and (ii) Instantaneous replenishment with quadratic time dependent carrying cost. Numerical examples are provided to illustrate the proposed model. Sensitivity analysis of the optimal solution with respect to the parameters of the system is carried out. The second order approximation is used for finding closed form optimal solution. Mathematica 5.2 software is used to find numerical results.

Due to increasing global warming and environmental consciousness, to avoid/reduce carbon emission is a challenge in today's business scenario. In this study, a three stage (buyer-distributer-vendor) economic order quantity strategy is presented. The objective of this study is to analyse the carbon emissions caused during transportation and holding of the inventory. In order to increase the utility of the proposed model, besides all cost parameters, carbon emission costs and transportation costs at every step of supply network are also considered as fuzzy and denoted by fuzzy numbers. Shortages are allowed and backlogged unconditionally for this study. The optimal solution are obtained by using (a non derivative) arithmetic geometric inequality method. Further the optimization model is studied under the following policies (i) without considering carbon emission and (ii) with carbon emission. Here closed form solutions are obtained. Proposed models are analysed environmentally and economically for the decision variables. A numerical example is used to demonstrate the work in a better way and obtained results are compared under both policies. Finally, the results of two models proved that, the model with carbon emission is better for cost reducing and environmental consciousness both. Sensitivity analysis is also performed with respect to all important parameters.

A recent paper finds that when volume discounts are available, in some cases, reliance on the Economic Order Quantity (EOQ) model can induce purchasers to make wealth reducing decisions, and the Present Value (PV) approach should be preferred. While this finding is theoretically correct, the magnitudes of wealth reductions suggested by the paper's numerical examples seem to be questionable. Furthermore, the paper also finds that, in some other cases, a purchaser using the EOQ approach realizes a net increase in current wealth compared to a purchaser using the PV approach. Logic suggests that such a finding cannot be correct, since by its very definition, it is the PV approach that seeks to maximize the current wealth. We offer an alternative frame of comparison and a modified model to show that, under the paper's assumptions, the EOQ approach can never realize a net increase in current wealth compared to the current wealth generated by the PV approach. On the other hand, we also show that when typical values of the relevant parameters prevail, the additional costs imposed by the EOQ approach are not significant. Finally, we suggest that insofar as the PV approach requires greater administrative costs to implement, it may even be counterproductive to the goal of wealth maximization. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 377–389, 1998

To respond to the adoption of carbon pricing regulations, researchers and industry are developing low carbon inventory models that can meet emission reduction targets while maintaining company profits. The challenge is getting tougher when the company is still facing problems related to imperfect product quality. This research solves this problem by developing an economic order quantity (EOQ) model by considering several sources of carbon emissions, as well as the influence of the defective rates, different demand rates, selling price and holding cost for defective products, and shortages backorder. The objective function of the formulated mathematical model is to minimize the total costs which include the emission costs. A numerical example is developed to illustrate the model based on the previous data set. Sensitivity analysis is also carried out to validate the model and to learn more about the system characteristics. The total emissions are calculated and the affecting factors are identified.