Leader-follower Game in VMI System with Limited Production Capacity Considering Wholesale and Retail Prices

VMI (Vendor Managed Inventory) is a widely used cooperative inventory policy in supply chains in which each enterprise has its autonomy in pricing. This paper discusses a leader-follower Stackelberg game in a VMI supply chain where the manufacturer, as a leader, produces a single product with a limited production capacity and delivers it at a wholesale price to multiple different retailers, as the followers, who then sell the product in dispersed and independent markets at retail prices. An algorithm is then developed to determine the equilibrium of the Stackelberg game. Finally, a numerical study is conducted to understand the influence of the Stackelberg equilibrium and market related parameters on the profits of the manufacturer and its retailers. Through the numerical example, our research demonstrates that: (a) the market related parameters have significant influence on the manufacturer’ and its retailers’ profits; (b) a retailer’s profit may not be necessarily lowered when it is charged with a higher inventory cost by the manufacturer; (c) the equilibrium of the Stackelberg equilibrium benefits the manufacturer.Stackelberg Game;Supply Chain;Vendor Managed Inventory

Analysis of decentralized production-inventory system

"November 22, 1999."Includes bibliographical references (p. 30-32).René Caldentey, Lawrence M. Wein

Replenishment policies for a tree-type three echelon supply chain system

One of the common goals which most companies have is to maximize profits. There are two way to increase profit: increasing revenue or reducing cost. Lacking of ability to keep the cost down could potentially drive the companies out of the business. In recent years, many researchers have been paying more attention on improving supply chain system due to high potential of creating cost savings. The supply chain network considered in this research is a tree-type, three-echelon single producer, multiple distributors, and multiple retailers system. The goal of this research is to develop a replenishment policy which satisfies customers’ demand and minimizes the total production-inventory system cost. Three inventory models are developed here. First, tree-type, three-echelon distribution (producer, distributor and retailers) model with end customers’ backorders (TDB) at retailer’s level is developed. Second, the variation of downstream holding cost (DHV) is studied and a model is developed to investigate the effect downstream holding cost structure. Third, a model is developed to improve the retailer’s service rate (ISR). This model combines the features of TDB and DHV models together (allowable backorder and reduced delivery interval at retailer’s level). Operational schedules of TDB are constructed and the limitations of DHV model are established. The improvement in the ISR model is confirmed and demonstrated through numerical examples. Significance and conclusions of this research are highlighted along with an indication of future research

Effective Multi-echelon Inventory Systems for Supplier Selection and Order Allocation

Successful supply chain management requires an effective sourcing strategy to counteract uncertainties in both the suppliers and demands. Therefore, determining a better sourcing policy is critical in most of industries. Supplier selection is an essential task within the sourcing strategy. A well-selected set of suppliers makes a strategic difference to an organization\u27s ability to reduce costs and improve the quality of its end products. To discover the cost structure of selecting a supplier, it is more interesting to further determine appropriate levels of inventory in each echelon for different suppliers. This dissertation focuses on the study of the integrated supplier selection, order allocation and inventory control problems in a multi-echelon supply chain. First, we investigate a non-order-splitting inventory system in supply chain management. In particular, a buyer firm that consists of one warehouse and N identical retailers procures a type of product from a group of potential suppliers, which may have different prices, ordering costs, lead times and have restriction on minimum and maximum total order size, to satisfy stochastic demand. A continuous review system that implements the order quantity, reorder point (Q, R) inventory policy is considered in the proposed model. The model is solved by decomposing the mixed integer nonlinear programming model into two sub-models. Numerical experiments are conducted to evaluate the model and some managerial insights are obtained with sensitivity analysis. In the next place, we extend the study to consider the multi-echelon system with the order-splitting policy. In particular, the warehouse acquisition takes place when the inventory level depletes to a reorder point R, and the order Q is simultaneously split among m selected suppliers. This consideration is important since it could pool lead time risks by splitting replenishment orders among multiple suppliers simultaneously. We develop an exact analysis for the order-splitting model in the multi-echelon system, and formulate the problem in a Mixed Integer Nonlinear Programming (MINLP) model. To demonstrate the solvability and the effectiveness of the model, we conduct several numerical analyses, and further conduct simulation models to verify the correctness of the proposed mathematical model

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

Initial inventory levels for a book publishing firm = Kezdőkészletek egy könyvkiadó vállalatnál

Egy könyvkiadó vállalatot vizsgálunk. A kiadó kiadványait a szokásos értékesítési láncon (kis- és nagykereskedelem) keresztül értékesíti. A kérdés az, hogy egy új könyv példányait hogyan allokálja az értékesítési láncban. Feltételezzük, hogy a kereslet ismert, Poisson-eloszlású. A készletezés költségeit szintén ismertnek tételezzük fel. Cél a költségek minimalizálása. = The aim of the paper is to analyze a practical real world problem. A publishing house is given. The publishing firm has contacts to a number of wholesaler / retailer enterprises and direct contact to customers to satisfy the market demand. The book publishers work in a project industry. The publisher faces with the problem to allocate the stocks of a given, newly published book to the wholesaler and retailer, and to hold some copies to satisfy the customers direct from the publisher. The distribution of the demand is unknown, but it can be estimated. The costs consist of inventory holding and shortage, backorder costs. The decision maker wants to minimize these relevant costs. The problem can be modeled as a one-warehouse and N-retailer supply chain with not identical demand distribution. The problem structure is similar that of a newsvendor model. It is assumed that the demand distribution follows a Poisson distribution

Dual-Channel Warehouse and Inventory Management with Stochastic Demand

This study examines the inventory policy for the emerging dual-channel warehouse, which has a unique structure where the warehouse is divided into two areas: one for fulfilling online orders and the other for storing products and fulfilling offline orders. A multi-item inventory model was developed considering the warehouse capacity constraint, demand, and lead time uncertainty. Solution methods are provided for both uniform and normal distributions. Adopting the proposed inventory policy for a dual warehouse is cost effective and adds flexibility to the warehouse and supply chain. The study also offers managerial insights on some critical issues faced by companies operating in a dual-channel context

Optimal Inventory Policy in a Closed Loop Supply Chain System with Multiple Periods

Purpose: This paper aims to model and optimize the closed loop supply chain for maximizing the profit by considering the fixed order quantity inventory policy in various sites at multiple periods. Design/methodology/approach: In forward supply chain, a standard inventory policy can be followed when the product moves from manufacturer, distributer, retailer and customer but the inventory in the reverse supply chain of the product with the similar standard policy is very difficult to manage. This model investigates the standard policy of fixed order quantity by considering the three major types of return-recovery pair such as commercial returns, end- ofuse returns, end –of- life returns and their inventory positioning at multiple periods. The model is configured as mixed integer linear programming and solved by IBM ILOG CPLEX OPL studio. Findings: To find the performance of the model a numerical example is considered for a product with three Parts (A which of 2nos, B and C) for 12 multiple periods. The results of the analysis show that the manufacturer can know how much should to be manufacture in multiple periods based on Variations of the demand by adopting the FOQ inventory policy at different sites considering its capacity constraints. In addition, it is important how much of parts should be purchased from the supplier at the given 12 periods Originality/value: A sensitivity analysis is performed to validate the proposed model two parts. First part of the analysis will focus on the inventory of product and parts and second part of analysis focus on profit of the company. The analysis which provides some insights in to the structure of the model.Peer Reviewe

A coordination framework for distributed supply chains

Supply chain is a network of cooperating organizations that are involved through upstream and downstream linkages. Such a complex system cannot be modeled simply by mathematical equations without simplification of the problem. Recently, Multi-Agent System (MAS) is proposed as a modeling technique to represent supply chain networks. In fact, many application problems in MASs that are concerned with finding a consistent combination of agent actions can be formalized as Distributed Constraints Satisfaction Problem (DCSP). The main purpose of this paper is to propose a novel coordination framework by adopting the DCSP philosophy for distributed supply chains, which are modeled by MASs, subjected to uncertainties. Simulation results indicate that the proposed mechanism outperforms traditional stochastic modeling in solving supply chain dynamics in terms of total cost and fill rate of the system. © 2004 IEEE.published_or_final_versio