Inventory Optimization Model Research Articles

An optimal inventory model with interaction of lot size, production rate and lead-time in a fuzzy back-order system

This paper examines the decision-making about the interaction of lot size, production rate and lead time between a vendor and a buyer with the consideration of trade credit and fuzzy back-order rate. We assume that the lead time demand is distribution free and the back-order rate is triangular fuzzy number. An economic model is design to determine the optimal lot-size, production rate and lead time while minimizing system total cost. A minimax approach is applied to tackle the model and designed an iterative algorithm to obtain the optimal strategy. Numerical example and sensitivity analyses are given to demonstrate the performance of the proposed methodology and to highlight the differences between crisp and the fuzzy cases. This paper provides optimal decision support tools for managers in the form of mathematical model that improve operational, tactical, and strategic decision making in the fuzzy system. This paper aims to raise the awareness of managers with regard to realistic inventory problems.

The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations

In the era of the fourth industrial revolution, the international community is striving to establish a coordinated system to prevent fatal climate change in a global sense. As a result of such changes in business environments, a new issue, sustainability, has recently presented a paradigm shift and new research opportunity in which the theories and practices in traditional production and operations management are being reinterpreted and reapplied in relation to this emerging issue. Under this research background, we consider an optimal emission-trading problem under a cap-and-trade (CAT) emission regulation when the customers’ demand is given as an arbitrary probability distribution. Such a CAT approach to reduce the amount of emissions is a normative system for the sustainable production of manufacturing firms, which is also closely related to a well-known open innovation in literature of inventory management. Then, we formulate two stochastic inventory optimization models, which can be applied immediately for two famous CAT policies that exist in reality. In particular, our objective is to draw theoretical and practical implications for baseline credit emission regulations, which are innovative and government-led emission regulation policies, with a well-known newsvendor analysis. For our analytical results, we first show that our objective functions are piecewise linear and (quasi)-concave. Thus, it is found that there exists a unique optimal solution to the problem. Second, we successfully obtain the closed-form optimal solutions for the two models considered. Finally, we conduct a sensitivity analysis through a comparative static analysis to examine how the model parameters can affect the optimal solution in each model. All these analytical results and implications are consistent with previous studies in the literature, as well as with our insights for the models.

An optimal inventory model for perishable items under successive price discounts with permissible delay in payments

This article derives an optimal ordering policy for non-instantaneously deteriorating items under successive price discounts with delay in payments. Here successive price discounts is a strategy to sell almost all the items before decomposition. The cause of implementing this concept in the model is the fact that about 25% of vegetables and fruits of India gets decayed before selling, due to lack of facilities and awareness of business strategies, although poverty is its vital factor. Thus we propose to offer successive price discounts of 20% and 40% after selling the stock up to 50% and 90% respectively to raise the customer’s inflow and so also rotate the cycle early to avoid more deterioration. This type of business not only reduces the factory of decomposability but also saves the holding cost partially. In addition to, the delay in payment is another business strategy of the wholesaler by which he keeps the retailers in track and so also reduces the holding cost. In this case the wholesaler offers an interest-free credit period to the retailers till the settlement of the accounts. The retailers earn interest on selling the revenue during this opportunity. Supplier charges interest on the outstanding balance after exceeding the period. Besides the above, again the inventory cost does not remaining constant due to various factors like inflation, salary, house rent etc. so a time varying holding cost has been well thought out instead of constant holding cost. Once more customers’ flow not only depends upon the price instigating but also on timings, hence we assume an exponential demand function which depends on these variables. The main idea of the task is to determine optimal selling price, optimal refill schedule and optimal ordering quantity such that the total profit is maximized under exponential constraints. The literal idea of the work is (a) to avoid the deterioration through successive price discounts, (b) to attract the customers through successive price discounts, (c) to sell all the items through successive price discounts, (d) to rotate the cycle early through successive price discounts, (e) to keep the retailers in track through delay in payment, (f) to keep variable holding cost instead of constant holding cost due to market inflation, (g) to get the optimum results under exponential constraints.

Inventory optimization model considering consumer shift and inventory transshipment in dual-channel supply chains

In this paper we consider a dual-channel supply chain which consists of an online store and multiple independent retail stores. In this system, customer shift induces inventory competition while transshipment brings inventory cooperation, both of which inuences inventory optimization and control. Therefore we respectively construct inventory optimization models under the two situations: customer shift and inventory transshipment. Specifically, unilateral customer shift and inventory transshipment are considered, and a one-for-one replenishment strategy is applied. We first solve the equilibrium state probability of on-hand inventory through Markov chain theory, then optimize performance measure (i.e., the total costs) to obtain the optimal basic inventory level. Finally, we analyze the impact of customer shift rate and inventory transshipment rate on the inventory strategies through numerical simulation, and further compare the differences in inventory decisions between the above two situations, which prove that inventory cooperation brought by inventory transshipment is not necessarily better than inventory competition brought by customer shift. In addition, we discuss several insights that are evident from the parametric analysis of the model.

基于需求学习的多阶段动态折扣和库存优化研究——以服装销售为例

基于需求学习的多阶段动态折扣和库存优化研究——以服装销售为例

Employees Attrition Detection using PSONN

Raw materials, intermediate goods and finished goods are termed as inventories while considering it as portion of business’s assets which can be considered as prepared or are prepared for sale. One of the suitable solutions is to design optimal inventory model. Major concern of industry is to design suitable inventory model. Some of the existing inventory management research works are discussed in literature. But this field is still a big area of interest. Many research works uses artificial intelligence models for inventory management. One amongst the area for inventory management is worker behavior in a company. So, employees are taken into account to be as an inventory that contributes in growth of an organization. Employee Attrition may be a big issue for the organizations specially once trained, technical and key staff leave for a far better chance from the organization. This leads to loss to interchange a trained worker. Therefore, we use the present and past worker data to analyze attrition behavior of employees.

Inventory model optimization revisited: Understanding service inventories to improve performance

Services are increasingly important in the modern economy, for both service and manufacturing firms, yet inventory literature has been focused mainly on physical goods and, only a few studies have included services in optimization. On the other side, traditional service management literature relies on an extremely narrow definition of inventory that excludes services, because they are perishable. Thus, there is a lack of research in the link between inventory optimization and service management. However, according to a new service inventory approach, businesses components such as tasks or information, as different from physical goods, can be performed and stored in anticipation of service demand as a form of service inventory—that is, inventorying by anticipation rather than delaying the service. This article aims to contribute to this lack of research by proposing a service inventory optimization model that integrates a service orientation to optimize tasks and information to be performed in advance. In contrast with traditional inventory models, where the objective is to optimize physical items, in this approach physical products whenever included, constitute only mechanisms for service provision. This service inventory model contributes to optimize the quantity of tasks or information to be anticipated and thus provides benefits for customers.

Two Warehouse Optimal Inventory Model for Non-Instantaneous Deteriorating Items

In this article, an optimal ordering policy for the stock model of items, whose deterioration starts after a certain period of time under the  dispatching policy Last in First Out (i.e. LIFO) in owned and rented warehouses is presented  with the demand of the product increases up to a certain point and that remains constant, deterioration rate which depends on time and  inflation. The main aim of the present article is to find an optimal    inventory model, which minimizes the total stock cost. Finally, this model is analyzed through by numerical examples .Â

Multi-objective linear fractional inventory problem under intuitionistic fuzzy environment

In this paper, we have assumed an inventory multi-objective optimization model under intuitionistic fuzziness. In modelling, we have considered the situations where triangular intuitionistic fuzzy numbers used to express some of the input information which associated with decision variables. Further, a ranking function approach by considering linear and the nonlinear degree of membership functions have been used to obtain the crisp form of the fuzzy parameters. Finally, the fuzzy goal programming approach has been used to solve the resultant model to obtain the optimal ordering quantity. Also, a comparative study of the formulated problem under intuitionistic fuzziness has been done with a deterministic model of inventory. The concept of the paper is explained through a numerical example.

Inventory simulation model of frozen-meat for food-safety program

This research discusses the application of inventory simulation and optimization model for food safety program in Indonesia. Frozen meat is a complementary commodity for fresh meat that has an inadequate supply in the country. The disadvantage of frozen meat is that it needs to be stored in a refrigerator to maintain its quality and thus increases the cost. Therefore, an appropriate inventory policy is crucial to minimize the cost. In order to deal with this situation, a Monte Carlo simulation followed by an optimization model is proposed. Specifically, the Moving Average and the Winter Methods are used to predict the demand in the future. The results show the best inventory policy thus the cost is minimized and the national needs are satisfied.

OPTIMIZATION OF ATM AND BRANCH CASH OPERATIONS USING AN INTEGRATED CASH REQUIREMENT FORECASTING AND CASH OPTIMIZATION MODEL

In this study, an integrated cash requirement forecasting and cash inventory optimization model is implemented in both the branch and automated teller machine (ATM) networks of a mid-sized bank in Turkey to optimize the bank’s cash supply chain. The implemented model’s objective is to minimize the idle cash levels at both branches and ATMs without decreasing the customer service level (CSL) by providing the correct amount of cash at the correct location and time. To the best of our knowledge, the model is the first integrated model in the literature to be applied to both ATMs and branches simultaneously. The results demonstrated that the integrated model dramatically decreased the idle cash levels at both branches and ATMs without degrading the availability of cash and hence customer satisfaction. An in-depth analysis of the results also indicated that the results were more remarkable for branches. The results also demonstrated that the utilization of various seasonal indices plays a very critical role in the forecasting of cash requirements for a bank. Another unique feature of the study is that the model is the first to include the recycling feature of ATMs. The results demonstrated that as a result of the inclusion of the deliberate seasonal indices in the forecasting model, the integrated cash optimization models can be used to estimate the cash requirements of recycling ATMs.

OPTIMIZATION OF ATM AND BRANCH CASH OPERATIONS USING AN INTEGRATED CASH REQUIREMENT FORECASTING AND CASH OPTIMIZATION MODEL

In this study, an integrated cash requirement forecasting and cash inventory optimization model is implemented in both the branch and automated teller machine (ATM) networks of a mid-sized bank in Turkey to optimize the bank’s cash supply chain. The implemented model’s objective is to minimize the idle cash levels at both branches and ATMs without decreasing the customer service level (CSL) by providing the correct amount of cash at the correct location and time. To the best of our knowledge, the model is the first integrated model in the literature to be applied to both ATMs and branches simultaneously. The results demonstrated that the integrated model dramatically decreased the idle cash levels at both branches and ATMs without degrading the availability of cash and hence customer satisfaction. An in-depth analysis of the results also indicated that the results were more remarkable for branches. The results also demonstrated that the utilization of various seasonal indices plays a very critical role in the forecasting of cash requirements for a bank. Another unique feature of the study is that the model is the first to include the recycling feature of ATMs. The results demonstrated that as a result of the inclusion of the deliberate seasonal indices in the forecasting model, the integrated cash optimization models can be used to estimate the cash requirements of recycling ATMs.

Research on Ordering Strategy of Perishable Products with Variable Demand

This paper mainly considers the influence of price on demand for perishable products. According to the characteristics of products and the condition of demand, demand is a function of price elasticity. Under the premise of allowing the shortage, this study constructs optimal inventory control model of perishable products by introducing the lost order coefficient and solves the model, improves the traditional inventory model. Using optimization method, which deduces the optimal ordering cycle, the optimal order quantity and the total inventory cost, etc. Through the example for the deterioration rate and service level to sensitivity analysis, the results show that as deterioration rate increases, the total inventory cost and sale price are on the rise, while the unit profit is decreasing; The service level is directly proportional to the selling price, inversely proportional to the total inventory cost and unit profit. This research provides a theoretical basis for firms in the efficient inventory management.

An optimal joint maintenance and spare parts inventory model

Optimised maintenance of plant machineries is one of the important tasks to reduce plant operating cost. To carry out these maintenance tasks smoothly, development of spare parts inventory policy is the most prioritised issue. This research aims at the derivation of a joint maintenance and spare parts inventory model for a multi-component system. The decision variables are the order quantity and the ratio of ordering interval to preventive maintenance interval. We used block-based maintenance policy and periodic review inventory policy in this study. At first, a cost function is developed assuming that failure occurrences follow Poisson process with a constant failure rate and machine failures are non-repairable. Second, the model is further expanded for the case when failure occurrences follow non-homogeneous Poisson process and machine failures are repairable. The applicability of the developed models is demonstrated by numerical examples. Sensitivity analysis is also conducted to examine the effects of input parameters.

Research on the spare parts inventory control for agriculture inter-district field operation

With the development, more and more research has begun to focus on product service systems. Product service systems link tangible products with intangible services to improve the company’s competitiveness. As an important part of product service, after-sales service directly affects the company’s image and interests. In order to ensure a good after-sales service level, the manufacturing company sets up service district for each service provider. Each service provider is only responsible for providing the required spare parts within the service district, which guarantees the service level to some extent. However, due to the instability of demand, spare parts inventory of service providers often suffers from shortages or accumulation problems. Shortage of stocks will cause excessive demand delay penalty, and the accumulation of stocks will result in a large amount of funds. How to ensure the level of service, balance the shortage and accumulation of inventory, and reduce the cost of spare parts have become an urgent problem to be solved. In order to make full use of inventory and reduce the amount of funds used, this paper do the research on spare parts inventory optimization for inter-district transport. At the same time, taking into account the need of transport vehicles in transport, this paper considers the restrictions on transport vehicles. This paper studies the optimization of spare parts inventory for inter-district transport, taking into account the limitation of the capacity of transport vehicles. Due to the limited capacity of transport vehicles, the setting of transshipment priority should not only consider the distance between service providers, but also consider the relationship between the number of transshipments and the number of vehicles required. In order to minimize the cost of spare parts, the paper establishes an inventory optimization model with the inter-district transport, and presents a mathematical model for directly transporting spare parts without considering transport vehicles and a mathematical model that does not consider inter-district transport. We find that, whether to consider the restrictions of transport vehicles, system behavior can vary drastically.

An optimal EOQ inventory model for non-instantaneous deteriorating items with various time dependent demand rates and time dependent holding cost

An economic order quantity inventory model for non-instantaneous deteriorating items has been developed with cubic demand rate, cubic deterioration rate and time dependent holding cost. Shortages in inventory are allowed in this model. In shortage period, partial and complete backlogging cases are considered. The main objective of this model is to develop an optimal policy that minimizes the total average inventory cost and optimal order quantity. Numerical examples are used to illustrate the developed model

An optimal EOQ inventory model for non-instantaneous deteriorating items with ramp type demand rate, time dependent holding cost and shortages

An economic order quantity inventory model for non-instantaneous deteriorating items has been developed with ramp type demand rate, time dependent deterioration rate and time dependent holding cost. Shortages in inventory are allowed in this model, which is partially backlogged. The main objective of this model is to develop an optimal replenishment policy that minimizes the total average inventory cost. Numerical examples are used to illustrate the developed model.

Optimal Imperfect Production Inventory Model under Joint Effect of Machine Breakdowns and System Reliability

Optimal Imperfect Production Inventory Model under Joint Effect of Machine Breakdowns and System Reliability

Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk

Traditional supply chain inventory modes with trade credit usually only assumed that the up-stream suppliers offered the down-stream retailers a fixed credit period. However, in practice the retailers will also provide a credit period to customers to promote the market competition. In this paper, we formulate an optimal supply chain inventory model under two levels of trade credit policy with default risk consideration. Here, the demand is assumed to be credit-sensitive and increasing function of time. The major objective is to determine the retailer’s optimal credit period and cycle time such that the total profit per unit time is maximized. The existence and uniqueness of the optimal solution to the presented model are examined, and an easy method is also shown to find the optimal inventory policies of the considered problem. Finally, numerical examples and sensitive analysis are presented to illustrate the developed model and to provide some managerial insights.

Model analitičkog CRM-a u funkciji optimizacije maloprodajnih zaliha

Customer relationship management is a modern business philosophy that grew out of relationship marketing focusing on a consumer as an individual, i.e. on satisfying consumer needs in order to foster their loyalty and turn them into repeat customers. Although the primary goal of customer relationship management is to ensure the stability of revenue generation from a long-term partnership between a supplier and a consumer, it is also a philosophy that rationalizes operations primarily through reducing the costs of attracting new customers, thereby optimizing inventories. Inventory optimization involves adjusting the production process to the needs of consumers. In the modern retail environment, characterised by high level of competition, maintaining inventories not readily marketable can mean the difference between survival and going out of business. Therefore, modern retail systems tend to optimize inventory. Today, this would be impossible to do without the possibilities provided by CRM systems, in particular its subsystem, analytical CRM. Monitoring consumer behaviour in retail is within the scope of CRM system. Data obtained from such systems serve as the basis for inventory management. However, for inventory management to be possible, one has to consider which models, especially stochastic, can be used in inventory optimization. These models then need to be applied in the analytical subsystem of the CRM system. For such models to have use value, it is necessary to adjust the transaction part of the CRM system in terms of collecting the data needed for selected retail inventory optimization models. The answers to these and other questions relating to the use of analytical CRM in optimizing retail inventory are contained in the results of this research.