1,078 research outputs found

    Leveraging Information Sharing to Increase Supply Chain Configurability

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    As supply chains evolve beyond the confines of individual organizations, collaboration has become the Holy Grail in supply chain technology. It plays a key role in achieving flexibility and responsiveness. Information sharing between partners is a key determinant of collaboration. This paper investigates information sharing in four different supply chains—3PL, VMI, CPFR, and supply networks—and compares their information sharing structures, shared data objects, and information flow models. The results show how the various parameters of an information flow model constrain the level of collaboration. Further, the modeling exercise provides insights on how to configure a collaborative supply chain by leveraging information sharing

    Reducing the impact of demand process variability within a multi-echelon supply chain

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    Forrester analyzed Supply Chain and the different levels existing in it, as well as the participant companies and the role played by each of them inside the chain as a global group, and observed that small variations in end item demand caused oscillations that are amplified throughout the chain. This phenomenon, called the Bullwhip effect, has detrimental consequences on inventory levels and on all kind of inventory costs that may affect the added value of the activities throughout the logistics chain and ultimately affect the Net Present Value of all the activities in the chain. There is a set of collaborative supply chain structures which reduce these harmful consequences within the supply chain. The study presented in this paper quantifies how collaborative supply chain structures reduce the Bullwhip effect in terms of demand variability and inventory cost

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

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    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

    Research on the supply chain inventory management to GeN Garment Co. Ltd

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    The problem of production-distribution under uncertainty based on Vendor Managed Inventory

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    In this paper, a problem of managed inventory by the vendor in the production-distribution supply chain is presented based on the scenario. The main purpose of presenting the model of maximizing producer profit in a three-level supply chain network consisting of various strategic and tactical decisions under uncertainty. Due to the nonlinearity and NP-Hardness of the problem, meta-heuristic genetic algorithms, Whale optimization algorithm and league champions algorithm have been used. The results of problem solving show the high efficiency of meta-heuristic algorithms compared to accurate methods in solving the above model. So that the maximum percentage of relative differences between the methods mentioned with GAMS is less than 1%.Also, by solving the sample problems in larger sizes, it was observed that the league champions algorithm has the highest efficiency in terms of achieving the optimal value of the target function in a shorter time than the other algorithms used, with a useful weight of 0.998

    Vendor managed forecasting: A case study of small enterprise

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    Enterprises use supply chain management practices for improving business or supply chain performance. It is observed that supply chain technologies like VMI are now becoming an integral part of enterprise’s strategy. Even small and medium enterprises can adopt this practice and improve the performance of supply chain. This paper discusses vendor managed forecasting with the help of case study. It shows how a small enterprise improves supply chain performance by using demand related information obtained from retailer. The results obtained in the study shows that vendor managed forecasting in supply chain reduces the demand variation and improves inventory management significantly.Peer Reviewe

    Rapid replenishment at a consumer product goods manufacturer

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    Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2007.Includes bibliographical references (p. 74-75).Increasing supply chain velocity has adverse consequences for consumer product goods manufacturers, but creates value and flexibility for retail stores. This thesis outlines a case study of a rapid replenishment pilot project between the food manufacturer General Mills, Inc. and their retail customer Giant Eagle. We outline constraints that General Mills had to impose upon their customer so it could remain profitable and retain its efficient operating strategy. We offer recommendations to General Mills on how to grow and sustain their rapid replenishment business.by Deborah Eugenia Becker and Roman Viktorovich Korchagin.M.Eng.in Logistic

    From supply chains to demand networks. Agents in retailing: the electrical bazaar

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    A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version
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