• Korean Management Science Review
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• v.25 no.1
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• pp.107-121
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• 2008

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.556-563
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• 2008

One of the most important issues of managing a supply chain is to determine the inventory level whenever shortage is permitted and vendor is responsible fur management of the both buyer and supplier's inventory. We present two vendor managed inventory models in the form of two-echelon supply chain models for: 1) one buyer-one supplier problem, and 2) two buyers- one supplier problem. We assume that shortage is permitted. The proposed methods of this paper provides a simple condition, which makes it easy to decide when and how vendor managed inventory model costs less than traditional one. The paper is supported with some numerical examples to show the implementation of the proposed methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.105-111
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• 2017

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers' are assumed to have the common cycle time, and a vendor manages retailers' inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor's cost, retailer's cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.1
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• pp.141-150
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• 2014

Due to their accessibility and 24-hr availability, convenience stores are an integral part of daily lives. Because they sell a limited number of products and have small shelf space, shelf space allocation and inventory replenishment are important considerations for inventory management that critically affect profit. In this paper, we propose five solutions for the vendor-managed inventory problem of convenience stores that maximize profit while considering stock-out-based product substitutions. The performance of the proposed solutions is evaluated via simulation to reflect the demand uncertainty and marketing activity.

• Journal of the Korea Safety Management & Science
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• v.10 no.3
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• pp.217-225
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• 2008

The inventory routing problem (IRP) is an important area of Supply Chain Management. The objective function of IRP is the sum of transportation cost and inventory cost. We propose an Artificial Immune System(AIS) to solve the IRP. AIS is one of natural computing algorithm. An hyper mutation and an vaccine operator are introduced in our research. Computation results show that the hyper mutation is useful to improve the solution quality and the vaccine is useful to reduce the calculation time.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.362-372
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• 2008

Manufacturers, or vendors, and their customers continue to adopt vendor-managed inventory(VMI) program to improve supply chain performance through collaboration achieved by consolidating replenishment responsibility upstream with vendors. In this paper, we construct a mixed integer linear programming model and propose a genetic algorithm for the integrated inventory and routing problems with lost sales maximizing the total profit in the VMI supply chains which comprise of a single manufacturer and multi-retailer. The proposed GA is compared with the mathematical model on the various sized test problems with respect to the solution quality and computation time. As a result, the GA demonstrates the capability of reaching solutions that are very close to those obtained by the mathematical model for small problems and stay within 3.2% from those obtained by the mathematical model for larger problems, with a much shorter computation time. Finally, we investigate the effects of the cost and operation variables on the total profit of the problem as well as the GA performance through the sensitivity analyses.

• Journal of Distribution Science
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• v.15 no.8
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• pp.15-28
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• 2017

Purpose - Many researchers analyze VMI as a supply chain collaboration program to reveal its true value. Most of them focus on the dyadic relationship in two stage supply chain systems. This study examines the effect of VMI when it is applied to the different parts of three stage supply chain systems. Research design, data, and methodology - Based on three stage supply chain, this study compares three different systems including full VMI, partial VMI, and non-VMI by using mathematical models. The performances of three systems are compared with the numerical examples of the proposed supply chain models. Results - The numerical examples reveal that full VMI where the manufacturer controls inventories at all stages outperforms any other systems in terms of the system profit and enables all individual members to gain greater profits than non-VMI. Meanwhile, under partial VMI where VMI is implemented between the wholesaler and retailer, only these two members improve their performances and the manufacturer who does not belong to VMI makes less profit than even under non-VMI. This study also examines the impact of market size and profit margin on the system performance. Conclusions - The result of this study supports the common belief that VMI secures the best result when it is applied to the entire supply chain system. The additional findings from the numerical analysis are discussed.