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

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

Optimal consignment stocking policies for a supply chain under different system constraints

The research aims are to enable the decision maker of an integrated vendor-buyer system under Consignment Stock (CS) policy to make the optimal/sub-optimal production/replenishment decisions when some general and realistic critical factors are considered. In the system, the vendor produces one product at a finite rate and ships the outputs by a number of equal-sized lots within a production cycle. Under a long-term CS agreement, the vendor maintains a certain inventory level at the buyer’s warehouse, and the buyer compensates the vendor only for the consumed products. The holding cost consists of a storage component and a financial component. Moreover, both of the cases that the unit holding costs may be higher at the buyer or at the vendor are considered. Based upon such a system, four sets of inventory models are developed each of which considers one more factor than the former. The first set of models allows a controllable lead-time with an additional investment and jointly determines the shipping size, the number of shipments, and the lead time, that minimize the yearly joint total expected cost (JTEC) of the system. The second set of models considers a buyer’s capacity limitation which causes some shipments to be delayed so that the arrival of these shipments does not cause the buyer’s inventory to go beyond its limitation. As a result, the number of delayed shipments is added as the fourth decision variable. A variable demand rate is allowed in the third set of models. Uncertainty caused by the varying demand are controlled by a safety factor, which becomes the fifth decision variable. Finally, the risk of obsolescence of the product is considered in the fourth model. The first model is solved analytically, whereas the rest are not, mainly because of the complexity of the problem and the number of variables being considered. Three doubly-hybrid meta-heuristic algorithms that combine two different hybrid meta-heuristic algorithms are developed to provide a solution procedure for the rest of models. Numerical experiments illustrate the solution procedures and reveal the effects of the buyer’s capacity limitation, the effects of the variable demand rate, and the effects of the risk of obsolescence, on the system. Furthermore, sensitivity analysis shows that some of the system parameters (such as the backorder penalty, the extra space penalty, the ratio of the unit holding cost of the vendor over that of the buyer) are very influential to the joint system total cost and the optimal solutions of the decision variables

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

Vendor-Buyer Coordination in Supply Chains

Collaboration between firms in order to coordinate supply chain operations can lead to both strategic and operational benefits. Many advanced forms of collaboration arrangements between firms exist with the aim to coordinate supply chain decisions and to reap these benefits. This dissertation contributes to the understanding of the conditions that are necessary for collaboration in such arrangements and the benefits that can be realized of such collaboration arrangements. This dissertation focuses on the vendor-buyer dyad in the supply chain. We identify and categorize collaboration arrangements that exist in practice, based on a review of the literature and combine this with formal analytical models in the literature. An important factor in the benefits of collaboration is the benefit of reduced costs of transport, by realization of economies of scale in the context of capacity-constrained trucks. As a contribution to the understanding of the dependence of transport costs on the volume transported, we demonstrate how transport tariffs for orders of less-than-a-truckload in size on a single link can be deduced from a basic model. The success of a collaboration arrangement depends on agreement about the distribution of decision authority and collaboration-benefits. We study a collaboration arrangement in which the vendor takes responsibility for managing the buyer's inventory and makes it economically attractive to the buyer by offering a financial incentive, dependent on the maximum level the buyer permits to be stocked. This dissertation demonstrates that this incentive alignment leads to considerable cost savings and near-optimal supply chain decisions

THREE ESSAYS ON VENDOR MANAGED INVENTORY IN SUPPLY CHAINS

Vendor Managed Inventory (VMI), Consignment Inventory (CI) and a combination of both (C&VMI) are supply-chain sourcing agreements between a vendor and customer. VMI allows the vendor to initiate orders on behalf of the customer. In CI, the customer pays for the goods supplied by the vendor only upon use. The vendor under C&VMI decides customer-replenishments, and owns the goods replenished until they are deployed by the customer. Our thesis studies these agreements in three essays. The first essay considers a vendor V that manufactures a particular product at a unique location. That item is sold to a single retailer, the customer C. Three cases are treated in detail: Independent decision making (no agreement between the parties); VMI, whereby the supplier V initiates orders on behalf of C; and Central decision making (both Vendor and Customer are controlled by the same corporate entity). Values of some cost parameters may vary between the three cases, and each case may cause a different actor to be responsible for particular expenses. Under a constant demand rate, optimal solutions are obtained analytically for the customer's order quantity, the vendor's production quantity, hence the parties' individual and total costs in the three cases. Inequalities are obtained to delineate those situations in which VMI is beneficial. The problem setting in the second essay is the same with that of Essay 1, but the sourcing agreements investigated are now CI and C&VMI. In CI, as in the usual independent-sourcing approach, the customer has authority over the timing and quantity of replenishments. CI seems to favour the customer because, in addition, he pays for the goods only upon use. Under a C&VMI agreement, the vendor still owns the goods at the customer's premises, but at least can determine how much to store there. The second essay thus contrasts the cases CI and C&VMI, and compares each of them to a no-agreement case. General conditions under which those cases create benefits for the vendor, the customer and the whole chain are determined. Essay 3 investigates VMI and C&VMI separately for a vendor and multiple customers who face time-varying, but deterministic demand for a single product. In any of those agreements, the vendor seeks the best set of customers to achieve economies of scale. MIP models are developed to find that set of customers, and to determine the vendor's optimal production, transportation, and customer-replenishment quantities. The model for VMI is solved using a heuristic that produces two sub-models, and uses hierarchical solution approach for production, customer-replenishment and transportation decisions. C&VMI model is solved using Lagrangian relaxation. Various numerical examples are used to test the solution approaches used. In the mean time, the customers can guarantee to be no worse off under VMI or C&VMI than the no-agreement case by setting the right levels of maximum inventory. A model to determine those levels and a solution algorithm are also proposed in Essay 3. The first two essays can help a vendor or customer in a supply chain to determine the least costly sourcing option, which depends on the relative values of various cost parameters. A vendor with multiple customers can make use of the results in the third essay, which reveal the best possible economies of scale under VMI or C&VMI. Those customers can guarantee to be no worse of than traditional sourcing when they set the proposed levels of maximum inventory

Vendor managed inventory practices: a case in manufacturing companies

The implementation of the Vendor Managed Inventory (VMI) in the Malaysian manufacturing sector can be viewed as a solution to mitigate the increment of operational costs and low performance in customer services. Many factors contributed to the performance of the VMI programme, but only a few attempts was made to determine the contribution of the VMI elements on VMI performance. The objectives of this study were to investigate the level of VMI practices, organizational factors and VMI performance; and to examine the influence of type of product on VMI element and VMI performance. The study used qualitative approach, which data were gathered from semi-structured questions through interview process. There are 4 manufacturing companies listed in the Federation of Malaysian Manufacturers were selected for data collection purpose. The findings showed that high information sharing, moderate level of inventory control, close inventory location to customer premises,inventory ownership, mutual decision on inventory replenishment are among VMI practices in manufacturing companies. The respondents also confirmed that the influence of type of product characteristic onto VMI performance only to a limited extent. As a recommendation, supplier and customer must design their VMI program, which suit to product characteristics. Another important part is VMI agreement should be balanced between the need of supplier’s authority in controlling customer’s inventory and current capability of supplier. They should consider the flexibility of VMI system, especially the capability to reduce cost on behalf of the supplier and to provide better service to the customer

An analysis on vendor hub

Master'sMASTER OF SCIENCE (MANAGEMENT

Synchronizing the Retail Supply Chain

Dit proefschrift ontwerpt een retail supply chain, die beter en goedkoper is dan de gangbare. Dit wordt bereikt door de distributie te synchroniseren op de productie¬momenten. Goederen zouden direct uit productie al stroomafwaarts moeten bewegen, van fabrikant naar retailer, tegen lage kosten, in volle pallets en in volle auto’s en in hoeveel¬heden die groot genoeg zijn om de vraag tot het volgende productiemoment te dekken. Door de formules van de "Krantenverkoper" en die van de economische ordergrootte (EOQ) aan te passen aan een multi-echelon divergerend distributienetwerk, kan ook theoretisch worden bewezen dat het stroomafwaarts positioneren van voorraden inderdaad optimaal is en dat de voorraden daardoor zullen dalen. De huidige magazijnen van de leveranciers kunnen worden gereduceerd tot overslagpunten, waar goederen van de verschillende fabrieken van een leverancier worden samengebracht om rijden met vollere vrachtwagens mogelijk maken. Kleinere hoeveelheden kunnen leveranciers beter afleveren bij het dichtstbijzijnde distributiecentrum van een retailer, waarna de retailer zelf het deel met bestemming elders verder vervoert. Tenslotte kan de winkelbevoorrading worden aangepast aan de schapruimte, waardoor de werkwijze in de distributiecentra kan worden gerationaliseerd.Piet van der Vlist (1947) was born in Ouderkerk aan den IJssel. He received his high-school diploma from the Marnix Gymnasium in Rotterdam. Also in Rotterdam he graduated as Electronics Engineer at the University of Applied Sciences. He obtained a Master of Science in Electronics at the Delft University of Technology and one in Management Sciences at the University of Twente. He worked 15 years with the Dutch Ministry of Defense on the design and realization of the first generation digital communications systems. Then he joined Bakkenist Management Consultants and later Deloitte Consultancy, together for over 20 years. As consultant he was involved in numerous projects on Data exchange and Supply Chain redesign. Besides that, he was for 11 years (part-time) professor in ICT and Logistics at the Eindhoven University of Technology. Piet wrote and edited several books on data exchange and published numerous articles in business and scientific journals. A fairly good overview of his scientific career can be found in the "Liber Amicorum" that his friends wrote when he left Eindhoven University1. His current research interests lie in the design and management of retail supply chains, all the way from production down to the shelves. He found that the supply chain with the overall lowest costs requires synchronization of distribution to production and not the other way around as current practice seems to dictate. When he had to quit his jobs for health reasons, he finally found the opportunity to devote his time to research and extend the theory that supports Supply Chain Synchronization. He programmed built to purpose simulation models to get a better insight in the dynamics of synchronized supply chains. He joined both the Rotterdam Erasmus University to work with Professor Jo van Nunen and the Eindhoven University of Technology to work with Professor Ton de Kok. This PhD thesis is the result of that effort.This thesis is a design of a retail supply chain that is better and cheaper than the usual one. This is achieved by synchronizing distribution to production. Right from production goods should move downstream the supply chain at low cost in full pallets and in full truckloads, in quantities large enough to cover the needs till the next production run. By extending both the Newsvendor- and the EOQ-formulae to a multi-echelon divergent network, it can be proved that such forward positioning of inventory indeed is optimal and that overall supply chain inventories will drop. The suppliers’ warehouses become stockless cross docking points, where goods from the supplier’s various sourcing plants are brought together to consolidate them into full truckloads. Whenever suppliers deliver lower volumes, they better bring these goods to the nearest retailer’s facility; thereafter the retailer himself should move these goods onward to the proper destination within the retailer’s network. And finally shop replenishment should be rationalized based on shelf coverage, so as to enhance the retailer’s warehouse operations