• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.44-51
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• 2017

In today's competitive environment, supply chain management is a major concern for a company. Two of the key issues in supply chain management are transportation and inventory management. To achieve significant savings, companies should integrate these two issues instead of treating them separately. In this paper we develop a framework for modeling stochastic programming in a supply chain that is subject to demand uncertainty. With reasonable assumptions, two stochastic programming models are presented, respectively, including a single-period and a multi-period situations. Our assumptions allow us to capture the stochastic nature of the problem and translate it into a deterministic model. And then, based on the genetic algorithm and stochastic simulation, a solution method is developed to solve the model. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.

• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.1-10
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• 2007

The objective of this study is to develop an optimal joint cost from the perspectives of both the manufacturer and the retailer. The integrated production-inventory model with Weibull distribution deteriorating items is assumed to have a constant demand rate. A limited retailer storage space and multiple delivery per order are considered in this model. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.750-755
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• 2014

Product shortage which causes backordering and/or lost sales cost is very popular in chemical industries, especially in commodity polymer business. This study deals with backordering cost in the supply chain optimization model under the framework of process-inventory network. Classical economic order quantity model with backordering cost suggested optimal time delay and lot size of the final product delivery. Backordering can be compensated by advancing production/transportation of it or purchasing substitute product from third party as well as product delivery delay in supply chain network. Optimal solutions considering all means to recover shortage are more complicated than the classical one. We found three different solutions depending on parametric range and variable bounds. Optimal capacity of production/transportation processes associated with the product in backordering can be different from that when the product is not in backordering. The product shipping cycle time computed in this study was smaller than that optimized by the classical EOQ model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.102-113
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• 2004

This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of vehicle is determined. A distribution system is consisted of a distribution center and many retailers. The model is assumed that the time horizon is discrete and finite, and the demand of retailers is dynamic and deterministic. Products are transported from distribution center to retailers according to transportation planning. Cost factors are the transportation cost and the inventory cost, which transportation cost is proportional to transportation distance of vehicle when products are transported from distribution center to retailers, and inventory cost is proportional to inventory amounts of retailers. Transportation time to retailers is represented as a genetic string. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. A mathematical model is developed. Genetic algorithm procedure is suggested, and a illustrative example is shown to explain the procedure.

• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.333-339
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• 2010

It is difficult to determine an optimal inventory level of aircraft engine and modules to achieve the target operational availability since F100-PW-200 & 229 engines of the F-16 & KF-16 aircraft are consisted of 5 modules with different failure rates and costs. This study presents a decision model, combining an integer programming problem and a regression metamodel. Data for the metamodel was attained from results of a simulation model, that represents operational and repair process of F-16 and KF-16. The objective function of an integer programming problem is maximizing the operational availability, representing pessimistic circumstances. Finally, an integer programming problem with a metamodel can make an optimal decision of the inventory level.

• Journal of the military operations research society of Korea
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• v.18 no.2
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• pp.181-191
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• 1992

In this paper in order to prevent break of operation of equipments resulted from the delay of parts supply, the continuous review(Q, r) inventory model with probabilistic lead time is developed. If the lead tire is random varivable, the cycle also is stochastic. Then it is not easy to obtain the total cost equation of this inventory model. Therefore it is assumed that one cycle is the interval of reorder points. When the lead time is assumed to have exponential probability distribution, the lot-size and reorder point which minimize total cost are obtained. And as the lead time increases, the order quantity and the total cost are greater, but the reorder point increases by a certain point of time and then decreases.

• Journal of Korean Institute of Industrial Engineers
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• v.14 no.2
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• pp.11-23
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• 1988

A periodic review inventory model for deteriorating items in which time is treated as a discrete variable is developed. The model is developed under deterministic but time dependent demands and instantaneous delivery. Deterioration is assumed to be a constant fraction of the on hand inventory and partial returns are allowed for the deteriorated items. The solution procedures for obtaining the optimal order quantities which maximize the total profit in the scheduling period are presented for the cases of back orders and lost sales. Finally, when the additional orders are allowed, an efficient solution algorithm determining the initial and additional order quantities and additional ordering time is developed. Some numerical examples are also presented to illustrate the results.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.904-913
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• 2005

This paper deals with an integrated problem of inventory control and dynamic pricing strategies for a commodity with price and sales-period dependent demand pattern, where a seller and customers have complete information of each other. The problem consists of two parts; one is each buyer's benefit problem which makes the best decision on price and time for buyer to purchase items, and the other one is a seller's profit problem which decides an optimal sales strategy concerned with inventory control and discount schedule. The seller's profit function consists of sales revenue and inventory holding cost functions. The two parts are closely related into each other with some related variables, so that any existing general solution methods can not be applied. Therefore, a simplified model with single seller and two customers in considered first, where demand for multiple units is allowed to each customer within a time limit. Therewith, the model is generalized for a n-customer-classes problem. To solve the proposed n-customer-set problem, a dynamic programming algorithm is derived. In the proposed dynamic programming algorithm, an intermediate profit function is used, which is computed in case of a fixed initial inventory level and then adjusted in searching for an optimal inventory level. This leads to an optimal sales strategy for a seller, which can derive an optimal decision on both an initial inventory level and a discount schedule, in $O(n^2)$ time. This result can be used for some extended problems with a small customer set and a short selling period, including sales strategy for department stores, Dutch auction for items with heavy holding cost, open tender of materials, quantity-limited sales, and cooperative buying in the on/off markets.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.89-97
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• 2012

This paper considers a manufacturer with a two-station make-to-stock and make-to-order serial production system. The MTS facility produces a single type of component and provides components for the MTO facility that produces customized products. In addition to the internal demand from the MTO facility, the MTS facility faces demands from the spot market with the option of to accept or reject each incoming demand. This paper addresses a joint component inventory rationing and batch production control which maximizes the manufacturer's profit. Using the Markov decision process model, we investigate the structural properties of the optimal inventory rationing and batch production policy, and present two types of heuristics. We implement a numerical experiment to compare the performance of the optimal and heuristic policies and a simulation study to examine the impact of the stochastic process variability on the inventory rationing and batch production control.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.349-357
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• 2002

This research is basically deals with an inventory distribution system with several regional sales branches. Under the continuous review policy, each sales branch places an order to its supplier whenever on hand plus on order inventory falls on the order point, and the order quantity is received after elapsing a certain lead time. This research first shows the method how to apply the product with low lever of demand into the continuous review policy. For the application, we use an order level as the maximum level of inventory during an order cycle. Also we analyze the lost sales case as a customer behavior. Further we use variable demands and variable lead times for more realistic situation. Based on the above circumstances, the research mainly discusses those methods to decide the optimal order level, order point, and order quantity for each sales branch which guarantees the system wide goal level of service, while keeping the minimum level of the system wide total inventory.