One vendor and multiple retailers system in vendor managed inventory problem with stochastic demand

In many supply networks, the retailers are reluctant to share information about demand and inventory level to the vendor. This might lead to many difficulties for the vendor in establishing his own order/production plan. Vendor managed inventory (VMI) policy can help to solve that problem. By applying VMI, information sharing is not really a problem for the vendor anymore and this policy have been proven to help reduce total inventory cost as well as improve customer service level in the supply network. In this research, a VMI model for the system with one vendor and multiple retailers will be developed. The main target of the model is to determine the retailer’s lot size, the vendor’s lot size, the retailer cycle time, and the number of replenishments in a vendor cycle so as to minimise the total system cost. For solution purpose, simulation-optimisation technique using genetic algorithm is employed to help find optimal solutions for the decision variables. Numerical experiments are conducted to show the applicability of the proposed model. Sensitivity analysis is also conducted to examine the effects of some input parameters on the optimal solution

One vendor-one retailer in vendor managed inventory problem with stochastic demand

One of the basic problems in supply chain operation is lack of information exchanges related to inventory between vendor and retailer. Vendor managed inventory (VMI) provides a good approach to handle this problem. VMI has been proven to reduce cost and improve customer service level. This research aim is to develop a VMI model for the system with one vendor and one retailer to minimise the total system cost. The model is developed for (t, q) policy where the retailer’s cycle time is fixed. Due to the complexity nature of the model, simulation-optimisation using genetic algorithm is employed to determine the decision variables which are the retailer’s lot size, the vendor’s lot size, and the number of replenishments in a vendor cycle. Numerical experiments are conducted to show how the proposed model works. Sensitivity analysis is also conducted to understand the effects of some input parameters

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs)

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

Benefits of retailer-supplier partnership initiatives under time-varying demand:a comparative analytical study

This paper aims to help supply chain managers to determine the value of retailer-supplier partnership initiatives beyond information sharing (IS) according to their specific business environment under time-varying demand conditions. For this purpose, we use integer linear programming models to quantify the benefits that can be accrued by a retailer, a supplier and system as a whole from shift in inventory ownership and shift in decision-making power with that of IS. The results of a detailed numerical study pertaining to static time horizon reveal that the shift in inventory ownership provides system-wide cost benefits in specific settings. Particularly, when it induces the retailer to order larger quantities and the supplier also prefers such orders due to significantly high setup and shipment costs. We observe that the relative benefits of shift in decision-making power are always higher than the shift in inventory ownership under all the conditions. The value of the shift in decision-making power is greater than IS particularly when the variability of underlying demand is low and time-dependent variation in production cost is high. However, when the shipment cost is negligible and order issuing efficiency of the supplier is low, the cost benefits of shift in decision-making power beyond IS are not significant

Information Sharing for improved Supply Chain Collaboration – Simulation Analysis

Collaboration among consumer good’s manufacturer and retailers is vital in order to elevate their performance. Such mutual cooperation’s, focusing beyond day to day business and transforming from a contract-based relationship to a value-based relationship is well received in the industries. Further coupling of information sharing with the collaboration is valued as an effective forward step. The advent of technologies naturally supports information sharing across the supply chain. Satisfying consumers demand is the main goal of any supply chain, so studying supply chain behaviour with demand as a shared information, makes it more beneficial. This thesis analyses demand information sharing in a two-stage supply chain. Three different collaboration scenarios (None, Partial and Full) are simulated using Discrete Event Simulation and their impact on supply chain costs analyzed. Arena software is used to simulate the inventory control scenarios. The test simulation results show that the total system costs decrease with the increase in the level of information sharing. There is 7% cost improvement when the information is partially shared and 43% improvement when the information is fully shared in comparison with the no information sharing scenario. The proposed work can assist decision makers in design and planning of information sharing scenarios between various supply chain partners to gain competitive advantage

Optimal Supply Network with Vendor Managed Inventory in a Healthcare System with RFID Investment Consideration

Supply Chain Management in the healthcare sector faces several significant challenges, including complexity in healthcare systems, high supply chain costs, balancing quality and costs, delay in delivery, product availability from vendors, inventory waste, and unpredictability and uncertainty. Among those challenges, having an effective inventory management system with an optimal supply network is important to improve the match between supply and demand, which would improve the performance of for healthcare firms. Vendor Managed Inventory (VMI) system is a replenishment solution in which the vendor monitors and decides the time and the quantity of the inventory replenishment of their customers subject to their demand information exchange. A VMI contract in the location-inventory assignment problem is a decision tool for management in the healthcare industry, in which it enables the management to have a cost and service effective decision tool to critically re-evaluate and examine all areas of operations in a SC network looking for avenues of optimization. This dissertation is based on a real-world problem arising from one of the world\u27s leading medical implant supply company applied to a chain of hospitals in the province of Ontario. The chain of hospitals under study consists of 147 hospitals located in Ontario, Canada. The vendor is a supplier of three types of medical implants (a heart valve, an artificial knee, and a hip). In Chapter 2 of this dissertation, we present an optimal supply healthcare network with VMI and with RFID consideration, in which we shed light on the role of the VMI contract in the location-inventory assignment problem and integrate it with both the replenishment policy assignment and the Radio Frequency Identification (RFID) investment allocation assignment in healthcare SC networks using both VMI and direct delivery policies. A numerical solution approach is developed in the case of the deterministic demand environment, and we end up with computational results and sensitivity analysis for a real-world problem to highlight the usefulness and validate the proposed model. We extend our research of integrating the VMI contract in the location-inventory assignment problem with the replenishment policy assignment under a deterministic demand environment to include the stochastic demand environment. The impact of the uncertainty of the demand as a random variable following two types of distributions, normal and uniform distributions, is studied in Chapter 3. Motivated by the lack of investigations and comparative studies dealing with the preference of dealing with VMI contracts to other traditional Retailer Managed Inventory (RMI) systems, we provide in Chapter 4 of this dissertation a comparative study in which we compare the total cost of the VMI system with another two situations of traditional RMI systems: first, a traditional RMI system with a continuous replenishment policy for all hospitals and with assigned storage facilities and second, a traditional RMI system with a direct delivery policy for all hospitals without assigning a storage facility. Computational results, managerial insights, sensitivity analysis, and solution methodologies are provided in this dissertation. Keywords: Vendor Managed Inventory, healthcare system, location-inventory, RFID technology, supply-chain network, stochastic demand, location-inventory assignment problem, and retailer managed Inventory

On the inventory routing problem with stationary stochastic demand rate

One of the most significant paradigm shifts of present business management is that individual businesses no longer participate as solely independent entities, but rather as supply chains (Lambert and Cooper, 2000). Therefore, the management of multiple relationships across the supply chain such as flow of materials, information, and finances is being referred to as supply chain management (SCM). SCM involves coordinating and integrating these multiple relationships within and among companies, so that it can improve the global performance of the supply chain. In this dissertation, we discuss the issue of integrating the two processes in the supply chain related, respectively, to inventory management and routing policies. The challenging problem of coordinating the inventory management and transportation planning decisions in the same time, is known as the inventory routing problem (IRP). The IRP is one of the challenging optimization problems in logis-tics and supply chain management. It aims at optimally integrating inventory control and vehicle routing operations in a supply network. In general, IRP arises as an underlying optimization problem in situations involving simultaneous optimization of inventory and distribution decisions. Its main goal is to determine an optimal distribution policy, consisting of a set of vehicle routes, delivery quantities and delivery times that minimizes the total inventory holding and transportation costs. This is a typical logistical optimization problem that arises in supply chains implementing a vendor managed inventory (VMI) policy. VMI is an agreement between a supplier and his regular retailers according to which retailers agree to the alternative that the supplier decides the timing and size of the deliveries. This agreement grants the supplier the full authority to manage inventories at his retailers'. This allows the supplier to act proactively and take responsibility for the inventory management of his regular retailers, instead of reacting to the orders placed by these retailers. In practice, implementing policies such as VMI has proven to considerably improve the overall performance of the supply network, see for example Lee and Seungjin (2008), Andersson et al. (2010) and Coelho et al. (2014). This dissertation focuses mainly on the single-warehouse, multiple-retailer (SWMR) system, in which a supplier serves a set of retailers from a single warehouse. In the first situation, we assume that all retailers face a deterministic, constant demand rate and in the second condition, we assume that all retailers consume the product at a stochastic stationary rate. The primary objective is to decide when and how many units to be delivered from the supplier to the warehouse and from the warehouse to retailers so as to minimize total transportation and inventory holding costs over the finite horizon without any shortages

A distributed coordination mechanism for supply networks with asymmetric information

The paper analyses the problem of coordination in supply networks of multiple retailers and a single supplier, where partners have asymmetric, private information of demand and costs. After stating generic requirements like distributedness, truthfulness, efficiency and budget balance, we use the apparatus of mechanism design to devise a coordination mechanism that guarantees the above properties in the network. The resulting protocol is a novel realisation of the widely used Vendor Managed Inventory (VMI) where the responsibility of planning is at the supplier. We prove that together with the required generic properties a fair sharing of risks and benefits cannot be guaranteed. We illustrate the general mechanism with a detailed discussion of a specialised version, assuming that inventory planning is done according to the newsvendor model, and explore the operation of this protocol through computational experiments

A Stochastic Process Study of Two-Echelon Supply Chain with Bulky Demand Process Incorporating cost Sharing Coordination Strategies

This research considers a single-item two-echelon supply chain facing a sequence of stochastic bulky customer demand with random order inter-arrival time and random demand size. The demand process is a general renewal process and the cost functions for both parties involve the renewal function and its integral. The complexity of the general renewal function causes the computational intractability in deciding the optimal order quantities, so approximations for the renewal function and its integral are introduced to address the computational complexity. Asymptotic expansions are commonly used in the literature to approximate the renewal function and its integral when the optimal decisions are relatively large compared to the mean of the inter-renewal time. However, the optimal policies do not necessarily fall in the asymptotic region. So the use of asymptotic expansions to approximate the renewal function and its integral in the cost functions may cause significant errors in decision making. To overcome the inaccuracy of the asymptotic approximation, this research proposes a modified approximation. The proposed approximation provides closed form functions for the renewal function and its integral which could be applied to various optimization problems such as inventory planning, supply chain management, reliability and maintenance. The proposed approximations are tested with commonly used distributions and applied to an application in the literature, yielding good performance. By applying the proposed approximation method to the supply chain cost functions, this research obtains the optimal policies for the decentralized and the centralized cases. The numerical results provide insights into the cost savings realized by the centralization of the supply chain compared to the decentralized case. Furthermore, this research investigates coordination schemes for the decentralized case to improve the utilities of parties. A cost sharing mechanism in which the vendor offers the retailer a contract as a compensation of implementing vendordesired inventory policy is investigated. The sharing could be realized by bearing part of the retailer’s inventory holding cost or fixed cost. The contract is designed to minimize the vendors cost while satisfying the individual rationality of the retailer. Other forms of coordination mechanisms, such as the side payment and delayed payment, are also discussed