Two Warehouses Inventory Model with Quadratic Demand and Maximum Life Time

This paper deals with a two warehouses inventory model with quadratic demand. Due to some seasonal products, all time retailers not fulfill the demand of customers, so to solve this difficulty retailer storage some product for future sales in out of season. Here we consider two warehouses system, Own Warehouse (OW) and Rent Warehouse (RW). This paper considers maximum life time for the products and shortages are not allowed. Mathematical model of this paper is proposed to obtain the total cycle time and minimum inventory cost. A numerical example is give to validate this proposed model

Controllable deterioration rate for time-dependent demand and time-varying holding cost

In this paper, we develop an inventory model for non-instantaneous deteriorating items under the consideration of the facts: deterioration rate can be controlled by using the preservation technology (PT) during deteriorating period, and holding cost and demand rate both are linear function of time, which was treated as constant in most of the deteriorating inventory models. So in this paper, we developed a deterministic inventory model for non-instantaneous deteriorating items in which both demand rate and holding cost are a linear function of time, deterioration rate is constant, backlogging rate is variable and depend on the length of the next replenishment, shortages are allowed and partially backlogged. The model is solved analytically by minimizing the total cost of the inventory system. The model can be applied to optimizing the total inventory cost of non-instantaneous deteriorating items inventory for the business enterprises, where the preservation technology is used to control the deterioration rate, and demand & holding cost both are a linear function of time

DETERIORATING INVENTORY MODEL WITH CONTROLLABLE DETERIORATION RATE FOR TIME-DEPENDENT DEMAND AND TIME-VARYING HOLDING COST

Abstract: In this paper, we develop an inventory model for non-instantaneous deteriorating items under the consideration of the facts: deterioration rate can be controlled by using the preservation technology (PT) during deteriorating period, and holding cost and demand rate both are linear function of time, which was treated as constant in most of the deteriorating inventory models. So in this paper, we developed a deterministic inventory model for non-instantaneous deteriorating items in which both demand rate and holding cost are a linear function of time, deterioration rate is constant, backlogging rate is variable and depend on the length of the next replenishment, shortages are allowed and partially backlogged. The model is solved analytically by minimizing the total cost of the inventory system. The model can be applied to optimizing the total inventory cost of non-instantaneous deteriorating items inventory for the business enterprises, where the preservation technology is used to control the deterioration rate, and demand & holding cost both are a linear function of time

A Fuzzy Two-warehouse Inventory Model for Single Deteriorating Item with Selling-Price-Dependent Demand and Shortage under Partial-Backlogged condition

In this paper we have developed an inventory model for a single deteriorating item with two separate storage facilities (one is owned warehouse (OW) and the other a rented warehouse (RW)) and in which demand is selling- price dependent. Shortage is allowed and is partially backlogged with a rate dependent on the duration of waiting time up to the arrival of next lot. It is assumed that the holding cost of the rented warehouse is higher than that of owned warehouse. As demand, selling- price, holding- cost, shortage, lost- sale, deterioration- rate are uncertain in nature, we consider them as triangular fuzzy numbers and developed the model for fuzzy total cost function and is defuzzified by using Signed Distance and Centroid methods. In order to validate the proposed model, we compare the results of crisp and fuzzy models through a numerical example and based on the example the effect of different parameters have been rigorously studied by sensitivity analysis taking one parameter at a time keeping the other parameters unchanged

Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model

The classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. In this paper, a new policy entitled “Allocation-In-Fraction-Out (AIFO)” is proposed. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Consequently, three general two-warehouse inventory models for items that are subject to inspection for imperfect quality are developed and compared – each underlying one of the dispatching policies considered. Each sub-replenishment that is delivered to OW and RW incurs a distinct transportation cost and undertakes a 100 per cent screening. The mathematical formulation reflects a diverse range of time-varying forms. The paper provides illustrative examples that analyse the behaviour of deterioration, value of information and perishability in different settings. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning, but may also suggest outsourcing the inventory holding through vendor managed inventory

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

Two warehouse material location selection

As a company increases their use of warehouse, the excess inventory that cannot be stored in the owned warehouse are transferred to a third-party warehouse in which the company pays rent and transportation cost for storing items and moving items back to the production site. This research introduces the concept of material location selection that allocates materials to these two warehouses while minimizing the total storage and transportation costs. A two-warehouse material flow network model is formulated and then derived to generate five material location policies for evaluating the material flow situation of a real manufacturing company. The result showed that there is around 15%-40% cost saving that the company potentially obtains by systematically allocating materials to warehouses. A material location selection model is then proposed with a two-warehouse production planning model that accounts for workload dependent lead-time. In addition, an inventory rollback algorithm is given as means to bypass imperfect material movement information, in order to analyze inventory levels. Last, an application of the material location selection and production planning models is given as a potential extension of these models for determining an expansion size of the owned warehouse.Includes biblographical reference

Imperfect quality items in inventory and supply chain management

The assumption that all items are of good quality is technologically unattainable in most supply chain applications. Moreover, inventory theories are often built upon the assumption that the rates of demand, screening, deterioration and defectiveness are constant and known, even though this is rarely the case in practice. In addition, the classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. This PhD research aims to advance the current state of knowledge in the field of inventory mathematical modelling and management by means of providing theoretically valid and empirically viable generalised inventory frameworks to assist inventory managers towards the determination of optimum order/production quantities that minimise the total system cost. The aim is reflected on the following six objectives: 1) to explore the implications of the inspection process in inventory decision-making and link such process with the management of perishable inventories; 2) to derive a general, step-by-step solution procedure for continuous intra-cycle periodic review applications; 3) to demonstrate how the terms “deterioration”, “perishability” and “obsolescence” may collectively apply to an item; 4) to develop a new dispatching policy that is associated with simultaneous consumption fractions from an owned warehouse (OW) and a rented warehouse (RW). The policy developed is entitled “Allocation-In-Fraction-Out (AIFO)”; 5) to relax the inherent determinism related to the maximum fulfilment of the capacity of OW to maximising net revenue; and 6) to assess the impact of learning on the operational and financial performance of an inventory system with a two-level storage. Four general Economic Order Quantity (EOQ) models for items with imperfect quality are presented. The first model underlies an inventory system with a singlelevel storage (OW) and the other three models relate to an inventory system with a two-level storage (OW and RW). The three models with a two-level storage underlie, respectively, the LIFO, FIFO and AIFO dispatching policies. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Each lot that is delivered to the sorting facility undergoes a 100 per cent screening and the percentage of defective items per lot reduces according to a learning curve. The mathematical formulation reflects a diverse range of time-varying forms. The behaviour of time-varying demand, screening and deterioration rates, defectiveness, and value of information (VOI) are tested. Special cases that demonstrate application of the theoretical models in different settings lead to the generation of interesting managerial insights. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning,but may also suggest outsourcing the inventory holding through vendor managed inventory