• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.83-100
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• 2014

Retail shops often experience purchase dependence in which some items are purchased together by customers due to their unknown interior associations. This paper develops an inventory model considering partial backordering under purchase dependence and compares the performance of the inventory model that ignores purchase dependence. Computational analyses show that purchase dependence should be incorporated as an important factor of inventory replenishment policy because the impact of purchase dependence can be more significant as the lost portion of the unmet demand orders increases and the item set is more correlated in terms of order demand.

• Korean Journal of Mathematics
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• v.29 no.2
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• pp.371-386
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• 2021

This paper investigates two discrete time queueing inventory models with positive service time and lead time. Customers arrive according to a Bernoulli process and service time and lead time follow geometric distributions. The first model under discussion based on replenishment of order upto S policy where as the second model is based on order placement by a fixed quantity Q, where Q = S - s, whenever the inventory level falls to s. We analyse this queueing systems using the matrix geometric method and derive an explicit expression for the stability condition. We obtain the steady-state behaviour of these systems and several system performance measures. The influence of various parameters on the systems performance measures and comparison on the cost analysis are also discussed through numerical example.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.117-129
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• 2005

This paper considers a make-to-order inventory-production system in which customer orders are admitted only when the number of outstanding customer orders is below a value committed by the system. We deal with general distributions for the customer order Inter-arrival, production, and replenishment lead time processes. Monotonicities of the optimal average cost with respect to these distribution parameters are established using sample path coupling arguments. When distributions are given as an exponential one, we implement a sensitivity analysis on the optimal inventory policy and show that it has monotonicities with respect to system costs using dynamic programming.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.8-13
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• 2003

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives In a stationary Poisson process The problem Is formulated using METRIC-approximation in a combined approach of pricing and (S-1.S) Inventory policy, for which an iterative solution algorithm is derived with respect to the corresponding one-warehouse multi-retailor supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed The computational results show that the proposed algorithm is efficient and derives quite good decisions

• Korean Management Science Review
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• v.26 no.1
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• pp.171-182
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• 2009

We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.33-49
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• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.106-119
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• 2005

Uncertainties inherent in customer demand patterns make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. In this paper, we propose two intelligent adaptive inventory control models for a supply chain consisting of one supplier and multiple retailers, with the assumption of information sharing. The inventory control parameters of the supplier and retailers are order placement time to an outside source and reorder points in terms of inventory position, respectively. Unlike most extant inventory control approaches, modeling the uncertainty of customer demand as a stationary statistical distribution is not necessary in these models. Instead, using a reinforcement learning technique, the control parameters are designed to adaptively change as customer demand patterns change. A simulation based experiment was performed to compare the performance of the inventory control models.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.1-14
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• 2015

The purpose of this paper is to reveal two problems in the existing inventory systems in retail market, and to suggest a Two-Bin System under Automatic Ordering System considering only base-stock. Large retailers already have a sophisticated inventory system based on an automatic ordering principle. However, why does the out-of-stock (OOS) happen in large discount stores in spite of having a good inventory system? This paper suggests two systems after finding the root causes concerning the previous question. For evaluating the performance of each system, the random 200 data set in each sample group was generated from MINITAB 16 and obeyed the Poisson distribution. The existing inventory system in retail market cannot help generating OOS due to indwelling contradiction in itself. The reasons are the ordering deadline and the relationship between ordering quantity and base stock. This paper also demonstrates that these previous studies on inventory fall into the closed loop. Also the paper shows that the performance of the replenishment policy was better than traditional methods dealing with ordering quantity and base stock.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.382-392
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• 2006

Vendor-managed inventory policy(VMIP) is a supply-chain initiative where the supplier is authorized to manage inventories of items at retail locations. In VMIP, the supplier monitors sales and stock information at retail locations and makes decisions of inventory replenishment and transportation simultaneously. VMIP has been known as an effective supply chain strategy that can realize many of benefits obtainable only in a fully integrated supply chain. However, VMIP does not always lead to lower the supply chain cost. It sometimes generates the total supply chain cost higher than the traditional retailer-managed inventory policy (RMIP). In this paper, we perform a comparison study on RMIP and VMIP in the retail supply chain which consists of a single supplier and a number of retailers. We formulate mixed integer programming models for both RMIP and VMIP with vehicle routing problems and perform computational experiments on various test problems. Furthermore, we derive the conditions which guarantee the dominant position for VMIP with respect to total supply chain cost in the simple retail supply chain.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.75-86
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• 1989

Joint stocking and preventive age replacement policy is considered for non-repairable items assuming instantaneous replenishment. A recursive relationship among the optimal preventive replacement ages is obtained, which shows that the preventive replacement ages in a replenishment cycle form an increasing sequence due to the inventory carrying cost. Using this relationship, a procedure is given for determining how many units to purchase on each order and when to replace each unit after it has begun operating so as to minimize the total cost per unit time over an infinite time span. The problem can be simplified if equal preventive replacement ages are assumed, and the solution is very close to that of the original unconstrained problem.