• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.9-17
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• 2006

This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event simulation. The developed algorithm uses the configuration algorithm that can change decision variables and the stopping algorithm that can end simulation in order to satisfy the given objective value during single run. It tries to estimate an auto-regressive model for evaluating correctly the objective function obtained by a small amount of output data. We apply the proposed algorithm to M/M/s model, (s, S) inventory model, and known-function problem. The proposed algorithm can't always guarantee the optimal solution but the method gives an approximate feasible solution in a relatively short time period. We, therefore, show the proposed algorithm can be used as an initial feasible solution of existing optimization methods that need multiple simulation run to search an optimal solution.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.529-538
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are association rules, decision tree, clustering, neural network and so on. Association rule mining searches for interesting relationships among items in a riven large data set. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. We analyze Gyeongnam social indicator survey data using association rule technique for environmental information discovery. We can use to environmental preservation and environmental improvement by association rule outputs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.938-946
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• 2005

We study the firm's strategy to price its products and plan the spare parts manufacturing so as to maximize its profit and at the same time to fulfill its commitment to providing the customers with the key parts continuously over the relevant decision time horizon, i.e., the production plus warrantee period. To examine the research question, we developed and solved a two-stage optimal control theory model. Our analysis suggests that if the cost to produce the spare part during the warrantee period is more expensive than that during the production period, the firm should increase its sales price gradually throughout the production period to control its sales. In addition, during the production period it is optimal for the firm to produce the spare parts more than needed so that the overproduced spare parts can be used to partially meet the demand during the warrantee period. We conducted numerical analysis to investigate the sensitivity dynamics among key variables and parameters such as inventory holding cost, unit spare part production costs, part failure rate, and parameters in the demand function.

• Journal of Korean Institute of Industrial Engineers
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• v.17 no.1
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• pp.29-35
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• 1991

This paper deals with a production-inventory model for two-stage batch production system. We propose a lot-sizing scheme which combines the integer multiple lot requirements (IMLR) policy and the integer split lot requirements (ISLR) policy. An iterative search procedure for optimal decision variables is presented and numerical examples are solved to illustrate the validity of the model. The results show that the proposed scheme outperforms the existing policies.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.137-151
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• 2008

This paper deals with two shops dealing with single perishable product the fresh items are sold at a list price in the primary shop and the unsold items that have reached a certain allowed age are transferred to the secondary shop to be sold at a discounted price. It is assumed that the demand rates in two shops are Independent each other and can be expressed as a function of inventory level and price. With the objective of maximizing the profit under a Last-In-first-Out. (LIFO) issuing policy, we develop mathematical models for the following two cases : (1) opening primary shop only and (2) opening both primary shop and secondary shop. There are three decision variables, i.e., the reduced price in the secondary shop, the allowed age at the primary shop, and the order quantities at the primary shop. A solution procedure is developed based on tabu search and its validity is illustrated through a comparative study.

• Korean Management Science Review
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• v.33 no.4
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• pp.77-89
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• 2016

Due to recent proliferation of the mobile shopping channels, customers increasingly tend to purchase using online channel while experiencing physical products in offline shops. This phenomenon requires traditional offline retailers to consider integrating online channels. In this study, we propose strategic options for the traditional offline retailers regarding the online channel integration, and provide corresponding decision models to maximize the expected profits. We also investigate how the strategic options vary with the product characteristics, by categorizing the products based on inventory cost, demand uncertainty, and fitness to the online channels. By analyzing numerical examples we illustrate how the best online channel integration strategy should be differentiated depending on the product categories.

• Journal of Korean Physical Therapy Science
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• v.6 no.4
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• pp.179-185
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• 1999

We know that social psychologic factors important to make a decision on characteristic of back pain and prognosis. These facters have difficult to diagnosis of back pain and being protract the treatment session and which bring about a social problem caused the impairment compensation. Clinically, twenty low back pain patients, 8 organic pain group and 12 functional pain group have completed the MMPI(Minnesota Multiphasic Personality Inventory) and the results were as follows: l)Mean MMPI T-score of Hypochondriasis was 56.60(12.39, that of Depression was 57.95(7.71, and that of Hysteria was 57.50(7.15. and those of other scales were within normal range near to 50. 2)there was no significant difference between male and female groups on MMPI scales 3)The MMPI T-score of organic group was significantly higher than that of functional group on Hypochondriasis and Hysteria scale.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.440-449
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• 2013

We consider a reverse supply chain with a production facility and a recovery facility, and address the joint control of production and disposal decisions for sustainable operations. Demands are satisfied from on-hand inventory of serviceable products, replenished via manufacturing or remanufacturing. Sold products may be returned after usage and each returned product is disposed of or accepted for recovery. Accepted returned products are converted into serviceable products after remanufacturing process. Formulating the model as a Markov decision process, we characterized the structure of the optimal production and disposal policy as two monotone switching curves under a special condition. Three types of heuristic policies are presented and their performance is numerically compared.

• Journal of Distribution Science
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• v.11 no.6
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• pp.13-19
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• 2013

Purpose - This study aims to predict the audit reports of listed companies on the Tehran Stock Exchange by using meta-heuristic algorithms. Research design, data, methodology - This applied research aims to predict auditors reports' using meta-heuristic methods (i.e., neural networks, the ANFIS, and a genetic algorithm). The sample includes all firms listed on the Tehran Stock Exchange. The research covers the seven years between 2005 and 2011. Results - The results show that the ANFIS model using fuzzy clustering and a least-squares back propagation algorithm has the best performance among the tested models, with an error rate of 4% for incorrect predictions and 96% for correct predictions. Conclusion - A decision tree was used with ten independent variables and one dependent variable the less important variables were removed, leaving only those variables with the greatest effect on auditor opinion (i.e., net-profit-to-sales ratio, current ratio, quick ratio, inventory turnover, collection period, and debt coverage ratio).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.535-538
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• 2006

We consider a two-period airline revenue management problem where customers may act strategically. Specifically, we study a two-fare-class airline seat inventory allocation problem which allow for the possibility that a customer may decide to defer to purchase in the hope that a cheaper ticket than those currently on offer (expensive tickets) become available. We also allow for the possibility that some customer will buy a more expensive ticket if the cheaper tickets are not available. We show how to find the optimal booking limits in the presence of such strategic customer behavior and investigate the impact of such strategic customer behavior on the expected revenue. The results are compared with those by the expected marginal seat revenue (EMSR) heuristic approach (Belobaba, 1987, 1989) with strategic customer behavior.