Inventory ordering policies for mixed sale of products under inspection policy, multiple prepayment, partial trade credit, payments linked to order quantity and full backordering

The situation where serviceable products are sold together with a proportion of deteriorating products to consumers is rarely discussed in the literature. This article proposes an inventory model with disparate inventory ordering policies under a situation where a portion of serviceable products and a portion of deteriorating products are sold together to consumers (i.e. mixed sales). The ordering policies consider a hybrid payment strategy with multiple prepayment and partial trade credit schemes linked to order quantity under situations where no inventory shortage is allowed and inventory shortage is allowed with full backorder. The hybrid payment policy offered by a supplier is introduced into the classical economic ordering quantity model to investigate the optimal inventory cycle and the fraction of demand that is filled from the deteriorating products under inspection policy. Further, a new solution method is proposed that identifies optimal annual total profit with mixed sales assuming no inventory shortage and inventory shortage with full backorder. The impact of an inspection policy is investigated on the optimality of the solution under hybrid payment strategies for the deteriorating products. The validation of the proposed model and its solution method is demonstrated through several numerical examples. The results indicate that the inventory model along with the solution method provide a powerful tool to the retail managers under real-world situations. Results demonstrate that it is essential for the managers to consider inclusion of an inspection policy in the mixed sales of products, as the inspection policy significantly increases the net annual profit

Inventory lot-size policies for deteriorating items with expiration dates and advance payments

[[abstract]]For deteriorating items with seasonal demand, a supplier usually requests that the buyer (retailer) prepays a fraction of the acquisition cost as a deposit. The expiration date of a deteriorating item is an important factor in a buyer's purchase decision. Despite its importance, relatively little attention has been paid to the effects of the expiration date; the versions of economic order quantity models that are available consider fixed deterioration rates. This paper considers a more realistic situation where the deterioration rate of a product gradually increases as the expiration date approaches. In this paper, the optimal cycle time and the cycle fraction of no shortages are the decision variables that minimize the total cost. The total annual relevant cost is shown to be strictly pseudo-convex for each of the decision variables, which simplifies the search for the global solution to a local minimum. This paper provides an improvement on earlier work, as it provides an optimal rather than a near-optimal solution. Several numerical examples are provided to illustrate the behaviour of the model and to highlight some managerial insights.[[notice]]補正完

Inventory Model with Partial Backordering When Backordered Customers Delay Purchase after Stockout-Restoration

Many inventory models with partial backordering assume that the backordered demand must be filled instantly after stockout restoration. In practice, however, the backordered customers may successively revisit the store because of the purchase delay behavior, producing a limited backorder demand rate and resulting in an extra inventory holding cost. Hence, in this paper we formulate the inventory model with partial backordering considering the purchase delay of the backordered customers and assuming that the backorder demand rate is proportional to the remaining backordered demand. Particularly, we model the problem by introducing a new inventory cost component of holding the backordered items, which has not been considered in the existing models. We propose an algorithm with a two-layer structure based on Lipschitz Optimization (LO) to minimize the total inventory cost. Numerical experiments show that the proposed algorithm outperforms two benchmarks in both optimality and efficiency. We also observe that the earlier the backordered customer revisits the store, the smaller the inventory cost and the fill rate are, but the longer the order cycle is. In addition, if the backordered customers revisit the store without too much delay, the basic EOQ with partial backordering approximates our model very well

An enhanced approximation mathematical model inventorying items in a multi-echelon system under a continuous review policy with probabilistic demand and lead-time

An inventory system attempts to balance between overstock and understock to reduce the total cost and achieve customer demand in a timely manner. The inventory system is like a hidden entity in a supply chain, where a large complete network synchronizes a series of interrelated processes for a manufacturer, in order to transform raw materials into final products and distribute them to customers. The optimality of inventory and allocation policies in a supply chain for a cement industry is still unknown for many types of multi-echelon inventory systems. In multi-echelon networks, complexity exists when the inventory issues appear in multiple tiers and whose performances are significantly affected by the demand and lead-time. Hence, the objective of this research is to develop an enhanced approximation mathematical model in a multi-echelon inventory system under a continuous review policy subject to probabilistic demand and lead-time. The probability distribution function of demand during lead-time is established by developing a new Simulation Model of Demand During Lead-Time (SMDDL) using simulation procedures. The model is able to forecast future demand and demand during lead-time. The obtained demand during lead-time is used to develop a Serial Multi-echelon Inventory (SMEI) model by deriving the inventory cost function to compute performance measures of the cement inventory system. Based on the performance measures, a modified distribution multi-echelon inventory (DMEI) model with the First Come First Serve (FCFS) rule (DMEI-FCFS) is derived to determine the best expected waiting time and expected number of retailers in the system based on a mean arrival rate and a mean service rate. This research established five new distribution functions for the demand during lead-time. The distribution functions improve the performance measures, which contribute in reducing the expected waiting time in the system. Overall, the approximation model provides accurate time span to overcome shortage of cement inventory, which in turn fulfil customer satisfaction

The influence of financial conditions on optimal ordering and payment policies under progressive interest schemes

In many business-to-business transactions, the buyer is not required to pay immediately after the receipt of an order, but is instead allowed to postpone the payment to its suppliers for a certain period. In such a situation, the buyer can either settle the account at the end of the credit period or authorize the payment later, usually at the expense of interest that is charged by the supplier on the outstanding balance. Some payment terms, which are often referred to as trade credit contracts, contain progressive interest charges. In such cases, the supplier offers a sequence of credit periods, where the interest rate that is charged on the outstanding balance usually increases from period to period. If a buyer faces a progressive trade credit scheme, various options for settling the unpaid balance exist, where the financial impact of each option depends on the current credit interest structure and the alternative investment conditions. This paper studies the influence of different financial conditions in terms of alternative investment opportunities and credit interest structure on the optimal ordering and payment policies of a buyer on the condition that the supplier provides a progressive interest scheme. For this purpose, mathematical models are developed and analyzed

Modelos de Inventarios con Productos Perecederos: Revisión de la Literatura

This paper presents a review of the main characteristics of the mathematical modelsdeveloped by the scientific community in order to determine an optimal inventory policyfor deteriorating items. Thus, a classified bibliography of 390 articles published from2001 to 2014 in high-impact journals is submitted while considering the type of demandand deterioration, the integration of inventory and pricing decisions, the inclusionof shortage and/or the time value of money, the consideration of multiple items and/ormulti-echelon systems, and the incorporation of uncertain parameters other than demand.Finally, research questions not yet addressed by the research community in the field ofinventory control for deteriorating items are pointed out.En el presente artículo se lleva a cabo una revisión de las principales características estudiadas por la comunidad científica en el desarrollo de modelos matemáticos que buscan definir una política de inventario óptima para productos que se deterioran. De este modo, se referencian 390 artículos publicados a partir del año 2001 en revistas de gran impacto, teniendo en cuenta: el tipo de demanda y deterioro representado en los modelos matemáticos, el estudio de una política de precio óptima, la inclusión de faltantes y/o valor del dinero en el tiempo, el estudio de múltiples productos y/o dos o más eslabones de la cadena de suministro, y la utilización de parámetros o variables difusas. Finalmente, se identifican oportunidades de investigación que a la fecha no han sido abordadas por la comunidad científica en este campo del conocimiento

An economic order quantity model for imperfect and deteriorating items with freshness and inventory level-dependent demand

Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2023.Consumer purchasing behaviour is influenced by many factors. Depending on the circumstances, these factors may become relevant drivers of important supply chain decisions. Expiration dates have an influence on the purchasing decision of consumers for perishable goods. Another behavioural influence that stimulates demand is the volume of goods that are available on display as part of the purchase transaction. Furthermore, the fact that certain goods deteriorate over time must also be evaluated within the context of the study of perishable goods. The market is increasingly seeking goods that have no inherent defects or imperfections. This investigation seeks to determine the impact of imperfect quality, deterioration, freshness and inventory level and also, how those issues can be improved upon in workable situations. This paper proposes an inventory model that stipulates the demand as a function of freshness and the inventory level. In addition, the inventory depletes through both deterioration and demand, and the product quality is not always perfect. The objective of the inventory model is to maximise the system’s profit, hence the study has developed a theoretical mathematical model for imperfect and deteriorating items with freshness and inventory level-dependent demand. A numerical example was used to illustrate the practical application of the model in a real life environment. Sensitivity studies were conducted to determine the impact of changes or variations to the inputs that are used in the model. The findings were that the date of expiry, the elasticity of demand and the selling price of the perfect products are the main constituents that affect the profitability.Industrial and Systems EngineeringMEng (Industrial Engineering)Unrestricte

Early commercial mortgage terminations and real estate supply constraints

The early termination of commercial mortgages represents a financial risk for lenders. Default and prepayment risks are the two main options priced in the main literature, where competing risk models are adopted to analyze both risks simultaneously. In this research, we examines the impact of collateral underlying real estate supply constraints on early mortgage termination. To achieve this, we suggest three original ideas. First, as we need to estimate supply elasticities of office markets in the US, we develop a mismatch conceptual model estimating long run supply elasticity and computing the correlation between structural vacancy and supply constraints. The results imply that low controlling power of landlords reduces the flexibility in adjusting equilibrium vacancies to respond to market shocks. Second, we suggest adopting the installment option valuation model for pricing early mortgage termination options. Early mortgage termination (joint mortgage default and prepayment) is analogous to an American continuous installment option embedded with straddle or strangle like payoff as this can capture the decision path that keeps the option alive by making scheduled mortgage payments. Third, we suggest two pairs of early termination options: (1) mortgage default vs restructuring; and (2) full prepayment in cash vs defeasance in empirical analysis. The significant impacts of tightening property supply constraints on the likelihood of different types of early mortgage termination are proved. Overall, we expect that these three original ideas offer a helpful insight for mortgage originators and regulators as well as policymakers to manage related risk by including the geographical composition of collateral by supply constraints in risk models

Advances in Optimization and Nonlinear Analysis

The present book focuses on that part of calculus of variations, optimization, nonlinear analysis and related applications which combines tools and methods from partial differential equations with geometrical techniques. More precisely, this work is devoted to nonlinear problems coming from different areas, with particular reference to those introducing new techniques capable of solving a wide range of problems. The book is a valuable guide for researchers, engineers and students in the field of mathematics, operations research, optimal control science, artificial intelligence, management science and economics

Accountants\u27 index. Thirty-second supplement, January-December 1983, volume 2: M-Z

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