Inventory Model Research Articles

Simple heuristics for the joint inventory and pricing models with fixed replenishment costs

This study considers the joint inventory and pricing problem of a firm selling a single item over a multi-period planning horizon. A fixed replenishment cost is incurred whenever the replenishment decision is made. Period demands are considered to be non-stationary, stochastic, and price-dependent. The literature shows that the optimal policy in such a system is of an (s, S, p)-type. The implementation of this type of policy might be challenging in practice due to the prevailing computational difficulty in determining the optimal policy parameters. This study, therefore, aims to develop computationally efficient heuristic approaches for the joint inventory and pricing problem. The proposed heuristics provide different levels of flexibility in making inventory and pricing decisions. Furthermore, they are essentially built on the concept of the replenishment cycle and do not require solving a stochastic dynamic program. Our numerical study demonstrates the profit efficiency of the proposed heuristic approaches against the optimal policy. The results also indicate that firms lacking the technical ability to employ a dynamic pricing strategy might still gain significant profit improvement by only using a dynamic inventory control policy.

Inventory pricing model under different carbon emission policies

Considering carbon emission in inventory management model is a hot topic in current academic circles. Studying inventory pricing can provide managers with better managerial insights. Economic order quantity model mainly solves the inventory management problem of demand determination. However, due to the complex market environment in real life, it is difficult to meet the conditions of constant demand. In addition, with the enhancement of low-carbon awareness of enterprises, the study of pricing model based on low-carbon policies has also attracted the attention of a large number of scholars. The robust optimization theory is applied, the inventory pricing model of demand fluctuation under carbon cap, carbon tax and carbon cap-and-trade policies is considered, the robust equivalence form of the problem is studied. The profit comparison under different policies is given. Numerical experiments show that the carbon cap-and-trade policy can better control the carbon emission of enterprises.

Inventory model having preservation technology with fix lifetime under two level trade credit policy

Supply-chain management involves moving storage supplies from origin to consumption, with manufacturers running production based on quadratic demand, distributors and retailers monitoring inventory. When a new product is released, demand often rises linearly and then declines dramatically when an alternative becomes available. Shortages are not allowed. Players' inventory will decrease at a rate of (1/(1+m-t)), where m is fixed lifetime, greater than the replenishment time. Deteriorating goods experience constant mass loss or usefulness, but preservation technology can help the damaged item to be consumed. Retailers with direct customer relationships can reduce stock spoilage through good warehouses. Manufacturers' storage systems have a higher deterioration rate. Two-tier trade credit financing is examined in this model. Distributors offer specific credit terms to stores, while manufacturers provide a grace period for invoicing. Distributors and retailers must pay interest on unsold inventories if invoices aren't settled on time. An integrated storage system reduces costs by minimizing costs through multiple shipments from manufacturers to distributors and retailers, and by adjusting replenishment times for each player. The resolution process is designed so that the supply chain operator gets the best possible decision. Therefore, results are authorized using mathematical examples for different scenarios. Management decisions are suggested.

Using eddy-covariance to measure the effects of COVID-19 restrictions on CO2 emissions in a neighborhood of Indianapolis, IN

Eddy-covariance (EC) flux measurements in Indianapolis were used to quantify the impact of the COVID-19 lockdown on CO and CO2 emissions from a highway and a suburban neighborhood. CO2 fluxes were measured for 6 weeks pre-lockdown (January 22, 2020–March 3, 2020) and during lockdown (March 25, 2020– May 5, 2020) using EC instrumentation at 41 m AGL. Fossil fuel CO2 emissions (CO2ff) were estimated by calculating eddy diffusivity to obtain CO flux and then scaling by the CO:CO2ff emissions ratio (RCO). Flux measurements segregated by wind direction were compared to hourly emissions from the 2020 Hestia inventory model. The lockdown CO2ff average weekday emissions from the highway estimated by EC decreased by 51.5 ± 10.9% (11.2 ± 2.2 µmol m−2 s−1) compared to pre-lockdown, similar to Hestia’s estimate 56 ± 7% (12 ± 1 µmol m−2 s−1). The EC measurements detected a significant (2.2 ± 0.7 µmol m−2 s−1) but smaller magnitude decrease in CO2ff emissions from the suburban neighborhood. The daily cycles of CO2ff emissions were significantly correlated with Hestia estimates from the highway but not from the suburbs. This study demonstrates that EC flux towers and high-resolution inventory models in regions with mixed and spatially heterogeneous sources can quantify abrupt changes in sector- and source-specific CO2 fluxes.

Optimal production plan in a production inventory model under the coexistence of both green and regular products: A study on Indian textile industry

The necessity to restrict environmental pollution worldwide has led to the development and implementation of green products. Various sectors within the industrial domain are now placing emphasis on the creation of environmentally friendly products in order to minimize their impact on the environment. The textile industry, both in India and globally, significantly contributes to environmental pollution through the release of untreated effluents into water and the emission of carbon into the atmosphere. Consequently, the popularity of green apparel is steadily increasing as a means to alleviate this crisis. It has been reported that, despite customer preference for green apparel, factors such as the cost of these products and a lack of consumer awareness regarding their importance deter a significant portion of potential buyers from making purchases. In order to stimulate demand for green apparel, the government could implement a subsidy scheme and initiate advertising campaigns highlighting the benefits of using such products. In the market, green apparel and regular apparel are viewed as substitutes for one another and coexist. As a result, there is a constant price competition between these two types of products. This research examines the optimal inventory decisions of manufacturers in a production inventory model where both green and regular products are present and product substitution is allowed. The demand for both types of products is influenced by their respective selling prices. Furthermore, the level of greenness and the efforts put into advertising green products have positive effects on generating demand for these products. The resulting objective function in this model is non-concave, and the quantum behaved particle swarm optimization technique is utilized to solve the corresponding optimization problem. Additionally, Mathematica software has also been employed to verify the efficiency of the proposed solution algorithm. To provide economic validation of the proposed model, a numerical example is presented. Finally, a sensitivity analysis of the key parameters is conducted to gain insights into their impact on the optimal solution. The results indicate that strategic and well-executed advertising campaigns, along with government subsidy schemes, can boost the market for green products and generate greater profits for manufacturers.

A dual-rate production inventory model for deteriorating items: Addressing shortages with variable production cycles

A dual-rate production inventory model for deteriorating items: Addressing shortages with variable production cycles

A Production inventory model for deteriorating items with quadratic time dependent demand with two levels of Production

A Production inventory model for deteriorating items with quadratic time dependent demand with two levels of Production

A sustainable manufacturing–remanufacturing inventory model with price and green sensitive demand for defective and usable items

A sustainable manufacturing–remanufacturing inventory model with two production phases is presented in this study. In this two phases model, the first phase is used for manufacturing whereas the second phase is used for both manufacturing and remanufacturing. Keeping in mind about environment and price of products, it is presumed that market demand rate is influenced by the greenness of item and unit selling price simultaneously. Remanufacturing is performed for non-serviceable items i.e., defective items which are produced from imperfect production and used items that are purchased from the market. But the products for which remanufacturing cost is more than manufacturing cost are scraped off. In the production process carbon releases from setting up, manufacture and holding of the perfect items. To mitigate the carbon emission carbon tax regulation is imposed. Next, concavity of the profit function is driven through the pseudo concavity. Profit is maximized by minimizing the economic, environmental, and social effect. The models are illustrated by a numerical example and a sensitivity analysis is also elaborated for fixed parameters. Special cases are provided to compare the result with previous literature. The results shows that manufacturer wishes to engage in remanufacturing as remanufacturing cost continuously increases with respect time. Another important finding is that the manufacturer can choose remanufacturing as the cost is lower than manufacturing for saving environment. Finally, mathematical findings are listed and managerial implications are recorded.

A Closed-Loop Supply Chain Inventory Model with Carbon Emissions and Green Technology Investment

This paper proposes an inventory model that integrates a manufacturer and a retailer in a supply chain system. The model employs environmentally friendly technology investments to reduce the emissions produced in the process. Furthermore, the demand at the retailer's end is unpredictable, and green investments affect the average demand levels. This research aims to identify the optimal delivery lot, the number of deliveries, the Safety Factor, the level of green technology, and the collection level to maximize the joint total profit. Numerical examples illustrate the model's practical application, and algorithms are developed to solve the problem. Sensitivity analysis is used to determine the key model parameters' effect on the model's behavior. Green investments have been shown to reduce emissions and increase returns on second-hand goods, thus enhancing the environmental efficiency of supply chains.

Pengoptimalan Persediaan Bahan Baku Utama Untuk Mengatasi Tantangan Industri Menggunakan Metode Just In Time (JIT) Dan Silver Meal Heuristic Pada PT. Indonesia Plafon Semesta

The inventory problem that still occurs at PT Indonesia Plafon Semesta is the accumulation of resin and calcium raw materials which results in considerable losses. PT Indofon began to experience a buildup of resin raw materials in August amounting to 16,100Kg and for calcium amounting to 15,200Kg so that each month it soared until its peak in October, namely a buildup of 23,500Kg of resin, and 23,200Kg of calcium. The use of the right method for inventory control problems is Just In Time , which is a management strategy used to optimize the production process and product delivery by buying and producing only when needed and at the right time. Silver Meal Heuristic, a heuristic approach used in inventory control to determine the optimal lot size. The quantity of raw material orders using JIT is relatively more than the silver meal, but with JIT the supplier only needs to send 4-5 times, meaning that the company can save costs. The quantity and frequency obtained from data processing using silver meal is more optimal. However, the cost of raw material inventory incurred is quite large. For a decrease in efficiency costs by implementing a policy of making purchases with Just In Time (JIT) and is expected to save on raw material inventory costs. So that these cost savings can be allocated by the company to other costs.

An Inventory Model for Deteriorating Items with Stock-Dependent Demand under Fuzzy Lead Time and Partial Backlogging

For inventory management purposes, lead time refers to the amount of time it takes for a purchase order to be completed. Its effect is an important phenomenon in inventory management system. It also plays a significant role when lead time unknown to the decision makers. This paper deals with an inventory model for deteriorating items under fuzzy lead time. The stock dependent demand with partially backlogged shortages are considered in the proposed model. The total inventory costs for both crisp model and fuzzy model are derived. The fuzzy lead time is assumed to be triangular and trapezoidal numbers. The signed distance methods (SD) is used for defuzzification purpose. The developed model is validated with the help of numerical illustration under both crisp and fuzzy scenario. A pictorial presentation is furnished to explain the behaviour of the total inventory costs towards lead-crisp, lead-triangular and lead-trapezoidal values. Lastly a sensitivity analysis is performed to judge the sensitive behaviour of the total cost towards changes of the cost parameters.

Optimal profit in two-level trade credit eoq model with default risk and reminder cost under finite time horizon having time-dependent demand and deterioration

Trade credit is a type of promotional activity that generally increases demand and revenue but also invites default risk due to dishonest customers. Due to default risk, revenue is lost, and to overcome this, an arrangement is made to remind the defaulters. A retailer dealing with a perishable item wants to exhaust the stock quickly after a certain deterioration level. Demand and deterioration of the products are normally dynamic. The business period of seasonal products is uncertain. Considering these facts, we formulate and analyze a two-level trade credit inventory model, where the wholesaler and retailer give credit periods to their corresponding downstream customers. After a certain level of deterioration, the retailer increases the credit period for the customers for early stock exhaustion, and to reduce default risk, a reminder cost is introduced. These activities increase the profit. The mathematical models under different circumstances are formulated for different time horizons. Some existing results are deduced. The models are numerically solved using a parametric study and the Generalised Reduced Gradient method through LINGO 19.0 software. Some lemmas and theorems are deduced to establish the analytical outcomes. Trade-offs between the number of the business cycle, trade credit, and reminder cost against optimum profit are separately demonstrated. The results with and without reminder cost are compared, and it is shown that the model with reminder cost fetches more profit. Profit under different uncertain environments are evaluated, and they differ marginally. Some beneficial impacts are discussed.

Emission reduction investment for green products of a manufacturing system via optimal control theory and artificial hummingbird algorithm

Now, due to the global industrialization, carbon emission from the industrial section imposes a severe impact on the current environment. Due to the increasing awareness of environmental and sustainability issues, green products, also known as eco-friendly, include a considerable impact on the today’s market economy. Keeping mind of these two important issues of the current scenario, a production inventory model is developed in which time-dependent production rate is considered. In this work, the level of greenness of the products, selling price and time, influences the customers’ demand rate. Again, two different cases are considered due to the business assimilation of defectively manufactured items: rework and salvage policies. Additionally, the company uses pollution reduction technologies to lower emissions from the manufacturing firms in order to lower emission taxes. The Euler-Lagrange equation is used to solve an optimal control problem that arises in the model as time-dependent production rate is taken into the account. The optimisation problem corresponding to the proposed model is solved with the help of artificial hummingbird algorithm (AHA) as the system's average profit functions for both of the considered scenarios are highly nonlinear in nature w. r. to its decision variables. Further, the results obtained from AHA are compared with the help of other well-known metaheuristics. Finally, sensitivity analysis is conducted to arrive at meaningful conclusions and implications for the competent manager of the manufacturing firm.

A Three-Warehouse Inventory Model for Deteriorating Items to Study the Effective Preservation Cost and Green Investment Under Partial Substitution

A Three-Warehouse Inventory Model for Deteriorating Items to Study the Effective Preservation Cost and Green Investment Under Partial Substitution

Collaborative system model construction and simulation optimization of e-commerce enterprise supply chain

ABSTRACT With the rise and rapid development of the e-commerce industry, the pressure borne by the supply chain of e-commerce enterprises is increasing, which greatly increases the complexity and uncertainty of inventory management in the e-commerce supply chain. The study integrates system dynamics and collaborative supply chain inventory management to construct a new model. The study first uses the concept of system dynamics to optimize the supply chain inventory management system; then the collaborative supply chain is used to construct a system model by combining the optimized management system. The results show that the collaborative supply chain inventory management model constructed by the study can better accelerate the product turnover rate, improve the overall operational efficiency and market competitiveness of the supply chain, and can provide new support for the development of e-commerce enterprises.

A Replenishment Policy for an Inventory Model with Price-Sensitive Demand with Linear and Quadratic Back Order in a Finite Planning Horizon

A Replenishment Policy for an Inventory Model with Price-Sensitive Demand with Linear and Quadratic Back Order in a Finite Planning Horizon

Sustainability in a Reverse Logistics Inventory Model with Carbon Emission, Reliability and Credit Financing Policy

Sustainability in a Reverse Logistics Inventory Model with Carbon Emission, Reliability and Credit Financing Policy

An Inventory Model for Deteriorating Items with Price Dependent Demand Under Fuzzy and Neutrosophic Fuzzy Environment

This paper represents an inventory model of deteriorating items under fuzzy and neutrosophic environment without allowing shortages in inventory. Demand is price dependent and is compared between crisp, fuzzy and neutrosophic fuzzy demand. Realistically it is observed that although the cycle time of any supply chain system is uncertain but uncertainty is mainly dependent on the selling price. So, here we have compared the model using crisp, fuzzy and neutrosophic fuzzy demand. The result is illustrated with the help of numerical example under fuzzy and neutrosophic fuzzy demand. KEYWORDS: Inventory, Fuzzy and Neutrosophic Fuzzy Price dependent Demand.

Uncertain random optimal control model for deteriorating inventory with the finite horizon

This paper examines a deteriorating inventory model with combined pricing and production during a limited selling time in an uncertain random setting. Demand is influenced by market size and price, which are portrayed in terms of random variables. The uncertainty factors affecting the inventory are represented by multiple Liu processes. Inventories deteriorate by a certain percentage and back-orders for inventories are permitted. This study aims to determine the optimal level of production rate and pricing that maximizes the producer’s total expected profit through the application of uncertain random optimal control theory, which is based on uncertain theory and probability theory. Numerical examples are used to compare joint pricing dynamic production model with dynamic production model under an optimal static price, highlighting the benefits of implementing joint pricing dynamic production model. Furthermore, it is evident that an increase in deterioration rate results in decreased on-hand inventory, yet higher production rate and price. It should also be noted that different levels of probability expectation of demand can have an impact on production inventory problem.

A comprehensive inventory management model with weibull distribution deterioration, ramp-type demand, carbon emission reduction, and shortages

This study examines the challenges of two warehouses operating under Last-In-First-Out (LIFO) order policies in inventory management, including unpredictable demand patterns, the decay of Weibull distribution, and the need to reduce carbon emissions by adopting green technology. The research addresses various shortage circumstances using advanced inventory modeling techniques to manage ramp-type demand and Weibull distribution deterioration. Additionally, it aims to reduce carbon emissions by incorporating environmentally friendly technologies. By combining advanced inventory modeling with green technology, businesses can effectively manage unpredictable market situations while actively contributing to the global initiative of reducing carbon emissions. It also takes into account various potential backlog scenarios. The proposed model also considers no, partial, and complete shortages and their combinations. This research aims to determine the optimal cycle duration for retailers to increase their total profit while simultaneously investing in green technology. A numerical illustration is provided, and a sensitivity analysis is performed in MATLAB on the optimal solutions concerning parameters to demonstrate applicability.