• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.91-108
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• 1998

Automated Storage and Retrieval Systems (AS/RSs) are an important facility for modern material management. The expected benefits of these capital-intensive facilities are gained when their control policies and their physical design parameters are determined simultaneously. In this paper we present several analytical models that capture the impact of the storage assignment policy and of the rack design on the expected storage and retrieval times. Sequential and interleaved service modes are considered for sequencing the storage and retrieval requests. We further investigate the impact of the rack structure on the relative performance of the following storage assignment policies : closest open location (random), full turnover-based policy, and class-based. Our analysis clearly indicates that significant savings in crane travel time are realized when implementing full turnover-based policy, rather than random. These savings become more and more pronounced as the profile of the storage racks approaches the square-in-time shape. Furthermore, it is shown that a class-based policy, with a small number of storage classes, will capture most of these savings and be easier to manage in practice.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.636-647
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.159-165
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• 2003

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. Since it has been known that traditional reorder policies sometimes show poor performance in distribution systems, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately f3r the 2-echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value fur general multi-echelon systems is very complex, we provide two approximation methods. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.995-1001
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• 2014

In the aftermath of the financial crisis of 2008, while numerous members of the general public lost their homes and jobs, many of the largest banks held responsible for the crisis have been successfully rescued by bailouts. In this paper, through the analysis of income inequality, unemployment, tax cuts, and bailouts, we show that the interests of the general public are different from the interests of politicians and bankers. While the small elite group of politicians and bankers could set the deregulation policies with inordinate power based on full information, most people were ignorant and unconcerned about the policies, and hence did not oppose them. Specifically, we model the credit change in the financial markets of the United States by a finite state machine, and design three local supervisors representing three groups with different interests. It is then shown that the deregulation policies were adopted according to the difference of the supervisors' powers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.71-77
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• 2009

Using the results of the expected busy periods for the dyadic Min(N, D) and Max(N, D) operating policies in a controllable M/G/1 queueing model, an important relation between them is derived. The derived relation represents the complementary property between two operating policies. This implies that it could be possible to obtained desired system characteristics for one of the two operating policies from the corresponding known system characteristics for the other policy. Then, upper and lower bounds of expected busy periods for both dyadic operating policies are also derived.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.1-15
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• 2023

This study compares and analyzes the legal systems of Korea, the European Union, China, and the United States based on the disclosure principles and processing policies for personal data processing and provides references for seeking improvements in our legal system. Furthermore, this research aims to suggest institutional implications to overcome data transfer limitations in the upcoming digital economy. Findings on a comparative analysis of the relevant legal systems for disclosing privacy policies in four countries showed that Korea's privacy policy is under the eight principles of privacy proposed by the OECD. However, there are limitations in the current situation where personal information is increasingly transferred overseas due to direct international trade e-commerce. On the other hand, the European Union enacted the General Data Protection Regulation (GDPR) in 2016 and emphasized the transfer of personal information under the Privacy Policy. China also showed differences in the inclusion of required items in its privacy policy based on its values and principles regarding transferring personal information and handling sensitive information. The U.S. CPRA amended §1798.135 of the CCPA to add a section on the processing of sensitive information, requiring companies to disclose how they limit the use of sensitive information and limit the use of such data, thereby strengthening the protection of data providers' rights to sensitive information. Thus, we should review our privacy policies to specify detailed standards for the privacy policy items required by data providers in the era of digital economy and digital commerce. In addition, privacy-related organizations and stakeholders should analyze the legal systems and items related to the principles of personal data disclosure and privacy policies in major countries so that personal data providers can be more conveniently and accurately informed about processing their personal information.

• Journal of Society of Preventive Korean Medicine
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• v.8 no.1
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• pp.147-153
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• 2004

This parer reviews the current situation on traditional medicine in the western pacific region. It mainly include government, scientific community and industry interests, national policies, practices and education, public financing systems and self-regulatory associations.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.145-153
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• 1999

We consider a Direct Input Output Manufacturing System(DIOMS) which has a munber of machine centers placed along a built-in Automated Storage/Retrieval System(AS/RS). The Storage/Retrieval (S/R) machine handles parts placed on pallets for the machine centers located at either one or both sides of the As/Rs. This report studies the operational aspect of DIOMS and determines the optimal operating policy by combining computer simulation and genetic algorithm. The operational problem includes: input sequencing control, dispatching rule of the S/R machine, machine center-based part type selection rule, and storage assignment policy. For each operating policy, several different policies are considered based on the known research results. In this report, using the computer simulation and genetic algorithm we suggest a method which gives the optimal configuration of operating policies within reasonable computation time.

• IE interfaces
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• v.17 no.3
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• pp.359-374
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• 2004

The objective of this paper is to provide an improved reorder decision policy for general multi-echelon distribution systems utilizing the shared stock information. It has been known that traditional reorder policies sometimes show poor performance in distribution systems. Thus, in our previous research we introduced the order risk policy which utilizes the shared stock information more accurately for the 2- echelon distribution system and proved the optimality. However, since the real world supply chain is generally composed with more than 2 echelons, we extend the order risk policy for the general multi-echelon systems. Since the calculation of the exact order risk value for general multi-echelon systems is very complex, we provide two approximation methods for the real-time calculation. Through the computational experiment comparing the order risk policy with the existing policies under various conditions, we show the performance of the order risk policy and analyze the value of the shared stock information varying with the characteristics of the supply chain.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.134-147
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• 2009

Tracking and exploiting instantaneous spectrum opportunities are fundamental challenges in opportunistic spectrum access (OSA) in presence of the bursty traffic of primary users and the limited spectrum sensing capability of secondary users. In order to take advantage of the history of spectrum sensing and access decisions, a sequential decision framework is widely used to design optimal policies. However, many existing schemes, based on a partially observed Markov decision process (POMDP) framework, reveal that optimal policies are non-stationary in nature which renders them difficult to calculate and implement. Therefore, this work pursues stationary OSA policies, which are thereby efficient yet low-complexity, while still incorporating many practical factors, such as spectrum sensing errors and a priori unknown statistical spectrum knowledge. First, with an approximation on channel evolution, OSA is formulated in a multi-armed bandit (MAB) framework. As a result, the optimal policy is specified by the wellknown Gittins index rule, where the channel with the largest Gittins index is always selected. Then, closed-form formulas are derived for the Gittins indices with tunable approximation, and the design of a reinforcement learning algorithm is presented for calculating the Gittins indices, depending on whether the Markovian channel parameters are available a priori or not. Finally, the superiority of the scheme is presented via extensive experiments compared to other existing schemes in terms of the quality of policies and optimality.