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• deposit-refund system for the circulation of RTIs (Returnable transport Items) to maximize supply chain profitability. • effects of RTI-related parameters to determine optimal policies under different retail price structures are investigated. • results lead to important implications for the design of deposit-refund systems for RTIs. While the use of Returnable Transport Items (RTI) is a common practice in supply chains committed to sustainability. An efficient RTI circulation mechanism must be implemented to ensure the profitability of the approach. Within this context, this paper presents a deposit-refund system (DRS) designed for RTI circulation to maximize supply chain profitability. The profit optimization analysis considered three scenarios: the vendor's profit, there tailer's profit, and the overall system profit. Tailored solution strategies are developed for each case, considering retail price components, and leading to the identification of the optimal deposit amount required to maximize RTI circulation. We further examinehow the retail price affects the profits of supply chain actors relative to the RTI return rate and studystudy how changes in return rates influence the profit patterns of supply chain actors. The results are scrutinized via several sensitivity analyses, leading to important implications for the design of deposit-refund systems for RTI. We for example find that the vendor's wholesale price has a significant effect in establishing the decision-maker's optimal policy in designing a DRS for RTI circulation. In other words, the wholesale price is a key component in assessing the economic viability and determining the deposit amount for RTI. Moreover, through a couple of hypothetical, butrealistic cases of RTI applications considering specific parameter settings, we shown that the vendor's position can be either significant or insignificant dependong on the difference between the value of the RTI and that of the goods it holds. [ABSTRACT FROM AUTHOR]

Perishable products in Europe, the United States, and Canada typically have expiration dates or maximum lifetimes assigned to them. As these products approach their predetermined lifetimes , there is a gradual increase in the rate of decay, leading to a reduction in their freshness. To examine the impact of these two distinct attributes on a perishable product with a predetermined expiration date, we introduce two inventory models that utilize a demand function incorporating a linearly decreasing price dependence and a nonlinear increase that is influenced by advertising. These models consist of: (i) a zero-ending stock scenario and (ii) a partially backlogged shortage situation. Under certain conditions, the optimal cycle length for the stock zero-ending model and the optimal period with positive inventory for the model with shortages are obtained. The frequency of advertisement is a discrete and integer decision variable, we devise two algorithms for both models to determine the optimal frequency of advertisement that maximizes the profit. Finally, we suggest some strategies in order to increase the profit by studying marginal insights from a sensitivity analysis. It is recommended that the manager focuses on creating more impactful advertisements that are affordable to promote the product's information through popular media channels. [ABSTRACT FROM AUTHOR]

• Buyer invests in the vendor's process to improve its competitive market position. • Develops an EOQ model with price dependent demand, analogous to head flow. • A faster learning rate than competitors ensures a prolonged profitability. • Improvements beyond learning-by-doing could be required for firms survivability. The economic order quantity model and its variants are the oldest reported scientific inventory models in the literature. They are mathematically simple to use and understand. This characteristic contributed to their popularity. However, they have limitations that restrict their application in practice. Researchers have extended those models by relaxing some of their restrictive assumptions. One of the main limitations of the EOQ model is the estimation of its cost parameters, such as setup and holding costs, which include some hidden (or difficult to estimate) components. Emerging research proposes using the second law of thermodynamics when to measure the hidden (entropy) costs of inventory systems. Another research stream focuses on learning-by-doing, which reduces the unit cost of a product, thus reducing its price and enhancing a firm's competitiveness. This paper assumes that a buyer receives a shipment from its vendor following the EOQ model. The buyer invests in the vendor's process to accelerate learning (mainly workers training, among other things). The buyer's unit purchase cost reduces because of learning at the vendor's side. The buyer's competitors also learn, increasing competitiveness. For this purpose, we develop an EOQ model where price-dependent demand is analogous to a heat transfer equation, which is used to determine the entropy cost. It accounts for improvement by learning as a result of the buyer's investment to compete in a market. The implementation and management of improvement programs are not usually smooth, resulting in disorder quantified by an entropy cost function. The developed EOQ model is investigated with and without entropy costs. Numerical results representing different scenarios are provided to illustrate the behavior of the models and identify the factors affecting the decision variables and, subsequently, the buyer's profitability. The results showed that in a competitive market, the buyer has to maintain a learning rate faster than those of its competitors to ensure a prolonged, but indefinite, profitability. The results also showed that investment in learning is meaningful when the competition is fierce. [ABSTRACT FROM AUTHOR]

This paper presents a two-period supply chain model which is comprised of one manufacturer and one retailer who are involved in trading a single product. The demand rate in each period is dependent on the selling prices of the current period and the previous period. We assume that the manufacturer acts as the Stackelberg leader and declares wholesale price(s) to the retailer who follows the manufacturer’s decision and sets his selling prices for two consecutive periods. The manufacturer adopts one of the two pricing options: (1) setting the same wholesale price to both the selling periods (2) setting different wholesale prices to two different selling periods. Based on these pricing options, we develop four decision strategies of the manufacturer and the retailer and compare them. For a numerical example, we study the effects of these decision strategies on the optimal results of the supply chain. Further, we graphically analyze under what circumstances a particular decision strategy plays a dominant role. [ABSTRACT FROM AUTHOR]

In the current global market, organizations use many promotional tools in order to increase their sales. One such tool is permissible delay in payments, i.e., the buyer does not have to pay for the goods purchased immediately rather can defer the payment for a prescribed period given by the supplier. This phenomenon motivates the retailer/buyer to order a large inventory lot so as to take full benefit of credit period. But the well decorated showroom (OW) with modern facilities has a limited storage capacity. Thus the retailer has to hire a rented warehouse to store the excess units. In this scenario, retailer usually adopts two types of dispatch policy: FIFO & LIFO, depending upon the situation, e.g., nature of items/deteriorating items, location of warehouse. Further in order to survive in the market, the retailer dynamically adjusts the prices of the goods to boost the demand and enhance the revenues. In the light of these facts, this paper develops an inventory model for deteriorating items with price-sensitive demand under permissible delay in payment in a two warehouse environment. Shortages are allowed and fully backlogged. The objective of this study is to find the optimal inventory and pricing policies so as to maximize the total average profit. Further, the different trade credit scenario has been exhibited with the help of a numerical example. A comprehensive sensitivity analysis has also been carried out to advocate the implication of FIFO and LIFO dispatch policy. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we determined product prices and designed an integrated supply chain operations plan that maximized a manufacturer’s expected profit. The computational results of this study revealed that as the variance of the demand distribution increases, a manufacturer will increase its inventory to levels that are greater than the anticipated demand to prevent the potential loss of sales and will simultaneously raise product prices to obtain a greater profit. In the cost minimization approach, the manufacturer may earn the highest possible profits, as determined by the profit optimization approach, only if this firm precisely forecasts the mean market demand for its products. Greater inaccuracies in this forecast will produce lower levels of expected profit. [Copyright &y& Elsevier]

Abstract: One of the interesting subjects in supply chain management is supply management, which generally relates to the activities regarding suppliers such as empowerment, evaluation, partnerships and so on. A major objective of supplier evaluation involves buyers determining the optimal quota allocated to each supplier when placing an order. In this paper, we propose a multi-objective model in which purchasing cost, rejected units, and late delivered units are minimized, while the obtained total score from the supplier evaluation process is maximized. We assume that the buyer obtains multiple products from a number of predetermined suppliers. The buyer faces a stochastic demand with a probability distribution of Poisson regarding each product type. A major assumption is that the supplier prices are linearly dependent on the order size of each product. Since demand is stochastic, the buyer may incur holding and stockout costs in addition to the regular purchasing cost. We use the well-known L-1 metric method to solve the supplier evaluation problem by utilizing two meta-heuristic algorithms to solve the corresponding mathematical problems. [Copyright &y& Elsevier]

Abstract: The article deals with a stochastic economic order quantity (EOQ) model over a finite time horizon where uniform demand over the replenishment period is price dependent. The selling price is assumed to be a random variable that follows a probability density function. As demand is probabilistic, stock out situation may occur. Based on the partial backlogging and lost sale cases during stock out period, the author develops the criterion for the optimal solution for the replenishment size such that the integrated expected profit is maximized. Moreover, the article suggests a new function regarding price dependent demand. Finally, numerical examples and its sensitivity analysis of key parameters are given to illustrate the proposed model. [Copyright &y& Elsevier]

Abstract: The article deals with an EOQ (economic order quantity) model over an infinite time horizon for perishable items where demand is price dependent and partial backorder is permitted. The rate of deterioration is taken to be time proportional and it is assumed that shortage occurs at starting of the inventory cycle. Based on the partial backlogging and lost sale cases, the author develops the criterion for the optimal solution for the replenishment schedule, and proves the optimal ordering policy is unique. Moreover, the article suggests to new functions regarding price-dependent demand and time varying deterioration rate. Finally, numerical examples are illustrated to test the model in various issues. [ABSTRACT FROM AUTHOR]