Vendor Managed Inventory Model Research Articles

An Analytical Decision-Making Model for Integrated Green Supply Chain Problems: A Computational Intelligence Solution

This paper presents an integrated mathematical decision-making model to reduce environmental footprints using process integration. By doing so, we address the research question: How can supplier selection, ergonomic factors, and green practices be integrated into mathematical decision-making models based on the vendor-managed inventory policy? We use the Branch and Bound method to provide optimal solutions and a metaheuristic optimization approach in computational intelligence for large-scale problems. This paper employs a multi-criteria decision-making method to compare proposed algorithms results based on six criteria. Our findings reveal that integrating the sourcing process with inventory decisions significantly improves cost performance. Furthermore, our results demonstrate that the proposed model effectively balances environmental and economic objectives using a carbon tax. Moreover, sensitivity analysis results indicate that optimizing water and energy consumption can significantly improve carbon footprints. In addition, the study shows that ergonomic factors, including lighting and temperature, have a substantial impact on performance. The primary contributions of this paper include the incorporation of a multi-sourcing strategy, green practices, ergonomic factors, and supplier selection into vendor-managed inventory decision models.

A new vendor-managed inventory four-tier model based on reducing environmental impacts and optimal suppliers selection under uncertainty

A new vendor-managed inventory four-tier model based on reducing environmental impacts and optimal suppliers selection under uncertainty

A vendor-managed inventory model for a three-layer supply chain considering exponential demand, imperfect system, and remanufacturing

This paper presents a vendor-managed inventory model for a three-layer supply chain comprised of suppliers, manufacturers, and retailers. This model considers an imperfect production system with a deterministic percentage of defective and deteriorated items, exponential demand for perishable products, and operational costs. The VMI model maximizes the benefits, assuming a Stackelberg approach to find the optimal values of replenishment lot sizes, production rates, selling prices, and product cycle length. A solution algorithm is developed to find the optimal solutions. A case study of the Dairy Industry for highly perishable products is provided to illustrate the applications, evaluate the performance, and obtain managerial insights. The results show that the percentage of defective and deteriorated items and remanufacturing rates are crucial in replenishment, production, and selling policies. The VMI agreement includes remanufacturing defective products to obtain new dairy derivates. The deteriorated products can be sold as near-expired products or inputs for compost, fertilizers, etc. Finally, some conclusions and future research lines are provided.

Carbon Emissions Effect on Vendor-Managed Inventory System Considering Displaced Re-Start-Up Production Time

Background: The classical mathematical formulation of the vendor-managed inventory (VMI) model assumes an infinite planning horizon, and consequently, the solution derived ignored the impact of the first cycle. The classical formulation is associated with another implicit assumption that input parameters remain static indefinitely. Methods: This paper develops two mathematical models for VMI for a joint economic lot-sizing (JELS) policy. Each model considers investment in green production, energy used for keeping items in storage, and carbon emissions from production, storage, and transportation activities under the carbon cap-and-trade policy. The first model underlies the first cycle, while the second underlies subsequent cycles. Results: The re-start-up production time for subsequent cycles commences only at the time required to produce and replenish the first lot, which implies further cost reduction. Mathematical formulations are perceived as important both for academics and practitioners. For example, the base model of the first cycle (subsequent cycles) generates an optimal produced quantity with 18.42% (4.35%) less total system cost when compared with the pest scenario in favor of the existing literature. Moreover, such a percentage of total system cost reduction increases as the production rate increases. Further, the proposed models not only produce better results but also offer the opportunity to adjust the input parameters for subsequent cycles, where each cycle is independent from the previous one. Conclusions: The emissions generated by the system are very much related to the demand rate and the amount of investment in green production. Illustrative examples, special cases, model overview, and managerial insights are given. The discussion related to the contribution of the proposed model, the concluding remarks, and further research are also provided. The proposed model rectifies the base model adopted by the existing literature, which can be further extended to be implemented in several interesting further inquiries related to JELS inventory mathematical modeling.

A New Vendor-Managed Inventory Model by Applying Blockchain Technology and Considering Environmental Problems

A New Vendor-Managed Inventory Model by Applying Blockchain Technology and Considering Environmental Problems

Analysis of Sub-Optimization Impact on Partner Selection in VMI

Different combinations of elements will lead to different system functions, so a supply chain composed of enterprises with different characteristics will lead to differences in the system performance. In this study, a vendor-managed inventory (VMI) model is built; the model takes into consideration the factors of demand amplification, order and inventory cost change. Then, the change in the revenue of the supply chain and its members—due to VMI—are represented, and the influence of the different production parameters on this change is analyzed. On the basis of proving the distinctive feature of the Kaldor–Hicks improvement possessed by VMI, the profit fluctuations of enterprises in a supply chain that is composed of members with different characteristics using VMI are calculated by a numerical experiment. The conclusions of this paper indicate why enterprises prefer to choose VMI partners, and the results confirm the sub-optimal characteristic of this tendency. In addition, the results also reveal the inherent contradiction of VMI between supply chain efficiency improvement and coordination among the supply chain’s members. If an enterprise chooses VMI partners solely to maximize its own interests, the possibility of Pareto improvement in the supply chain will be maximized. However, at this time, a more effective supply chain system cannot be organized.

Vendor managed inventory system considering deteriorating items and probabilistic demand for a three-layer supply chain

This paper proposes a Vendor Managed Inventory model for a three-layer supply chain comprised of multiple suppliers, manufacturers, and retailers. During the production and storage of products, rates of defective and deteriorated products are generated, respectively. The imperfect quality and deteriorating items are removed from the lot size. The decision variables include the replenishment cycles and production rates of finished products, order times, and raw materials production rates. It is assumed that deteriorating rates are constant, and the demand rates of retailers are probabilistic. A joint optimization model is developed to maximize the benefit function of the supply chain. Cost of order, deterioration, holding, screening, production, disposal, fixed, labor, purchasing, and others. A collaborative approach is considered among the chain members where the manufacturers lead the inventory policies to avoid risks associated with deterioration items. Moreover, the Taylor series expansion approximates the exponential terms, and a solution procedure is proposed to find the optimal solutions. A case study of the Dairy Industry for highly perishable products is provided to apply the VMI model and perform a sensitivity analysis. This collaboration scheme is developed according to confidentiality policies to share information related to sales forecast, operational cost, storage strategies, quality conditions, and increased product rotation to reduce deterioration. The results show greater participation of the retailers and manufacturers in the benefits of the chain, which is consistent with the VMI policy. Finally, the conclusion, managerial implications, and future research are presented.

A vendor-managed inventory model based on optimal retailers selection and reliability of supply chain

<p style='text-indent:20px;'>One of the most common and successful approaches for the integrated supply chain management (SCM) is the vendor-managed inventory (VMI). In VMI, a vendor takes control of the inventory decisions for retailers. To establish a long-run relationship between the vendor and the retailer, it is necessary to consider two impactful factors: the vendors and retailers' reliability, and the optimal selection of retailers. For this purpose, the redundancy allocation problem (RAP), as an effective technique for increasing the reliability of vendors, is used in this paper. Also, the reliability of retailers as well as the reliability of the relationship between retailers and vendors are considered. In the retailer selection, process decisions on impactful criteria are simultaneously considered. For the retailers' selection, one analysis hierarchical process (AHP) is performed for each vendor, and the weights of retailers are obtained. Then, the obtained weights are plugged into the model as the inputs of the designed model. Since the developed model is a non-differentiable, non-convex, and mixed-integer function, genetic algorithm (GA) and particle swarm optimization (PSO) are leveraged to solve the formulated model. Finally, the efficiency of the presented method is verified through a case study with data collected from the electronic supply chain.</p>

Developing trust among players in a vendor-managed inventory model for random demand under environmental impact.

Retailers play a vital role in supply chain management because they deal directly with consumers. Occasionally, retailers may cover the entire system's statistics and not disclose these data to the manufacturer. Therefore, asymmetry is generated in the data throughout the system. The main motive of this research was to prevent unreliability throughout the system using a vendor-managed inventory policy. This research shows that by applying a cap and trade policy, the total carbon emitted from the production and transportation sectors can be controlled in the atmosphere. Finally, numerical and sensitivity analyses, along with pictorial representations of various parameters, are performed to examine the optimal results of this study. In addition, the retailer's lead time demand for items is assumed to be random rather than fixed and follows uniform and normal distribution functions. Under these two distribution functions, the optimal retailer lot size, service provided by the retailer to customers, and retailer reorder points are assessed. Furthermore, an evaluation of the total carbon released from an environmental viewpoint is illustrated using numerical findings. The numerical results show that this research is 50.24% more economically beneficial than the methods used in previous studies, whereas the mean value of demand follows a uniform distribution.

Vendor-managed inventory (VMI) deteriorating item model taking into account carbon emissions

This paper investigates the main activities that lead to carbon emissions in a deteriorating items supply chain. This study applies a vendor-managed inventory (VMI) model for deteriorating items with a single-setup-single-delivery (SSSD) policy and a single-setup-multiple-delivery (SSMD) policy. We provide constructive managerial insights to both researchers and industries in their inventory management decisions in minimizing the total deteriorating items cost and the total carbon emissions. A numerical example is developed to optimize the delivery quantity and the number of deliveries per production cycle. The results enable companies to identify an effective inventory management critical to reducing carbon emissions, especially for deteriorating items.

A Vendor-Managed Inventory Model for Imperfect Production Process Using Sustainability Investment and Energy Consumption Under Different Carbon Policies

A Vendor-Managed Inventory Model for Imperfect Production Process Using Sustainability Investment and Energy Consumption Under Different Carbon Policies

A Single Supplier Multi Buyer Supply Chain Coordination under Vendor- managed Inventory: Ensuring Buyers’ Interests in a Decentralized Setting

Our work delves into supply chain coordination involving a single supplier selling a single product to multiple downstream buyers. We consider the case when the supplier proposes implementing vendor-managed inventory (VMI) for each buyer. The VMI contract involves the buyers charging a penalty to the supplier on the excess inventory whenever the supplier exceeds some pre-decided inventory threshold. Unlike the works covered predominantly in the VMI literature involving penalty, where both the penalty and the threshold are exogenous, we develop a model to determine both endogenously. In our study, the supplier deciding on the penalty and the inventory threshold needs to ensure that each of the buyers’ interests is protected, that is, none of the buyers becomes worse off from the optimal position, thereby ensuring the willing participation of all the buyers. We further compared our model with the centralized Joint Economic Lot Size (JELS) model and other existing models. We show that our model has a cost equivalence with the JELS model with unequal order intervals. We also show the superiority of our proposed model over the existing VMI models in terms of the overall costs. Finally, we examine the impact of size and ordering cost on each buyers’ costs through numerical analysis.

Vendor Managed Inventory Model in a Supply Chain with Single Vendor and Multiple Retailers Considering Price and Shelf Space Aspects

Vendor Managed Inventory Model in a Supply Chain with Single Vendor and Multiple Retailers Considering Price and Shelf Space Aspects

Collaborative vendor managed inventory model by using multi agent system and continuous review (r, Q) replenishment policy

In the vendor-managed inventory (VMI) system, the vendor takes over responsibility for managing customer inventory so that delivery is not based on the order but the customer's inventory condition. It makes the vendor becomes a dominant entity, and customers are supplied by its own vendor exclusively. That is why most studies in VMI implement a single-vendor-single-customer or single-vendor-multi-customer scenario. In certain conditions, this exclusiveness can increase lost sales. Besides, most of them implement a single product scenario. In this work, we develop VMI model for the multi-vendor-customer-product scenario. This model is developed based on the collaborative multi-agent system. The relationship between vendors and customers is many-to-many. This work aims to reduce lost sales and maintain efficiency in the inventory. The continuous review (r, Q) policy is used as the replenishment model. The simulation result shows that the collaborative model creates higher sales, lower lost sales, and competitive inventory than the non-collaborative one. The lost sales is 50 to 75 percent lower. The sales percentage is 17 to 27 percent higher. The total retailers' stock is 20 to 38 percent higher. The total vendors' stock is 11 to 30 percent lower. The total stock in the supply chain in the collaborative model is 2 to 16 percent higher. The number of retailers is directly proportional to the total vendor's stock and total supply chain stock gaps; inversely proportional to the lost sales gap; and not related to the sales percentage and total retailers' stock gaps.

A Vendor-Managed Inventory Model for Deteriorating Products

A Vendor-Managed Inventory Model for Deteriorating Products

Vendor Managed Inventory for Multi-Vendor Single-Manufacturer Supply Chain: A Case Study of Instant Noodle Industry

This paper develops a vendor-managed inventory (VMI) model for a multiple-vendor, single-manufacturer supply chain, in which the first stage members can be traders and/or producers and the second stage member is a manufacturer. The model utilizes a realistic transportation cost which is dependent on the sizes (small- or medium-sized) of trucks. It can determine suitable sizes and numbers of trucks that minimize the transportation cost. A genetic algorithm (GA) technique, implemented in MATLAB software, is used to determine the best solution to the problem. A case study in the instant noodle industry is conducted to demonstrate the usefulness of the proposed model. Based on the experimental results, the VMI model has reasonable behaviors using sensitivity analysis. To reduce the inventory level of raw materials, the penalty cost may be set at a relatively high level or the upper inventory limits may be set at relatively low levels, without significantly affecting the average total cost per period of the entire supply chain. When the vendors are allowed to make decision independently, the solution is still the same as the solution from the proposed VMI model, which means that the manufacture does not take advantage of the vendors.

Inventory Management Under Power Structures With Consignment Contract Subject to Inventory Inaccuracy

This paper focuses on who should control the inventory and who should lead the supply chain under consignment contract. The supply chain consists of one supplier and one retailer, and inventory inaccuracy occurs on the retailer's side. Vendor-managed inventory (VMI) and retailer-managed inventory (RMI) models are analyzed in two different supply chain power structures: where the supplier is the Stackelberg leader (referred as SVMI and SRMI) and where the retailer is the Stackelberg leader (referred as RVMI and RRMI). The inventory availability and the channel cost sharing rate are examined to investigate the impact of these two factors on supply chain performance under four cases. It is important to find that whatever the values of the inventory availability and the channel cost sharing rate may be, the retailer always prefers SVMI. However, there is a threshold value of inventory availability (channel cost sharing rate) such that the supplier prefers SVMI only if the inventory availability (channel cost sharing rate) is larger (less) than the threshold value; and it prefers RRMI only if the inventory availability (channel cost sharing rate) is less (larger) than the threshold value. Therefore, both leading retailer and leading supplier have the incentive to act as the follower.

A vendor managed inventory on consignment with penalty as a supply chain coordination arrangement

This paper presents a mathematical two echelon vendor-managed inventory (VMI) model on consignment scheme in supply chain, in which the vendor pays a penalty for every extra unit which exceeds a specific upper limit to the buyer. In this arrangement the vendor can decide about the batch size he wants to transship to the buyer. Two cases are discussed in this paper; single vendor-single buyer and single vendor-two buyers. In this study after a review of coordination in supply chain and VMI on consignment, we discuss vendor-managed inventory scheme in comparison with traditional inventory control system. The optimal batch size is calculated and the paper investigates how a VMI on consignment arrangement with penalty can coordinate the supply chain. Numerical examples and sensitivity analysis is presented to illustrate the performance of model and the results.

A New Hybrid Method for Optimizing Vendor-Managed Inventory Model

This research proposes an effective procedure that is considered in exact solution methods category for solving a nonlinear model of single-manufacturer multi-retailer with multi-product supply chain which uses vendor-managed inventory (VMI) policy. The objective is to maximize total profit for the vendor while satisfying retailers’ benefit under the various operational constraints. Since most of the time there are defective goods in each delivery, this model investigates the inspection and screening process in which imperfect quality items are rejected and the retailers may encounter the shortage at the end of each cycle. Due to complexity and nonlinearity of the model, in the first step genetic algorithm (GA) is used to generate a suitable solution. Then barrier algorithm with applying the steepest descent method (GA/barrier) is developed to further optimize the solution acquired by GA and to achieve the more efficient solutions concluding the wholesale and retail prices of items, replenishment cycles and backlogging rates as decision variables. At the end, the efficiency of GA/barrier and GA algorithms are compared together in a numerical example. The results show that GA/barrier algorithm is able to provide significantly more efficient solutions comparing to GA.

Improving sustainability in a two-level pharmaceutical supply chain through Vendor-Managed Inventory system

Hospitals, as the main customers of medications, typically adopt conservative inventory control policies by keeping large quantities of drugs in stock. Given the perishable nature of medications, such strategies lead to the expiration of excess inventory in the absence of patients’ demand. Consequently, producers are faced with governmental penalties and environmental reputation forfeit due to the negative impact that disposing expired medications pose to the environment. This article aims to improve the sustainability of a pharmaceutical supply chain using a real case study. An analytical model is proposed to explore the effect of implementing a Vendor-Managed Inventory (VMI) system in minimizing the quantity of the expired medications at hospitals. Further, a set of Monte-Carlo simulation tests are conducted to investigate the robustness of the VMI model under demand uncertainty. Experimental results on a real case study under deterministic demand show the efficiency of the VMI model in eliminating the amount of expired medications without compromising customer’s satisfaction. The results also demonstrate that the safety stock (SS) level and the capacity assigned to the customer are crucial factors in the overall cost of the pharmaceutical supply chain (PSC). The PSC cost could be reduced by 19% when reducing the SS level by 50%. Moreover, the producer is recommended to increase the capacity assigned to the customer by a factor of 1.5 so as to fully satisfy the customer’s demand. Finally, the simulation results confirm the efficiency and robustness of embracing a VMI system under random demand scenarios. More precisely, zero amount of expired medications is obtained in 93% of cases. Thus, adopting this strategy could minimize drug wastage and ultimately improve the reputation of the producer in the market in terms of implementing Lean and sustainable practices.