• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1503-1520
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• 2013

For multi-line insurance companies, allocating the risk capital to each line is a widely-accepted risk management exercise. In this article we consider several applications of the Euler capital allocation. First, we propose visual tools to present the diversification and the line-wise performance for a given loss portfolio so that the risk managers can understand the interactions among the lines. Secondly, on theoretical side, we prove that the Euler allocation is the directional derivative of the marginal or incremental allocation method, an alternative capital allocation rule in the literature. Lastly, we establish the equivalence between the mean-shortfall optimization and the RORAC optimization when the risk adjusted capital is the expected shortfall, and show how to construct the optimal insurance business mix that maximizes the portfolio RORAC. An actual loss sample of an insurance portfolio is used for numerical illustrations.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.59-79
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• 2010

This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.792-797
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• 2011

This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.190-197
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• 2013

People are living longer than ever before. As a result, life expectancy is going up and the demand of long-term care facilities is increasing in most countries. The facilities provide rehabilitative, restorative, and skilled nursing care to patients or residents in need of assistance with activities of daily living. This study deals with the capacitated location and allocation problem of long-term care facilities in a city that consists of a finite number of regions. Assuming that in each region candidate locations for three types of facilities are already given, two integer programming models are developed under the closest assignment rule reflecting the demand characteristics of the facilities. Both the location and type of the facilities to be built become decision variables. To show the validity of the models, numerical problems are solved with commercial software, CPLEX. Also, sensitivity studies were conducted to identify relationships between the system parameters.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.17-26
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• 2017

An anti-forensic data hiding method in an NTFS index record is a method designed for anti-forensics, which records data as a file name in index entries and thereafter the index entries are made to remain in the intentionally generated slack area in a 4KB-sized index record[7]. In this paper, we propose a maximum data allocation rule for an anti-forensic data hiding method in an NTFS index record; i.e., a computational method for storing optimal data to hide data in an index record of NTFS is developed and the optimal solution is obtained by applying the method. We confirm that the result of analyzing the case where the number of index entries n = 7 is the maximum case, and show the screen captures of index entries as experimental results.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.79-89
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• 1999

A counting rule that allows an element to be linked to more than one enumeration unit is called a multiplicity counting rule. Sample designs that use multiplicity counting rules are called network samples. Defining a network to be a set of observation units with a given linkage pattern, a network may be linked with more than one selection unit, and a single selection unit may be linked with more than one network. This paper considers allocation for multivariate stratified random sampling with multiplicity.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.41-50
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• 1989

This paper deals with the problem of space allocation of items within a warehouse. Recognizing the importance of weights associated with material handling, mathematical models are developed for two cases, out-and-back selection and storage retrieval interleaving. It is proved that the density order index rule we proposed generates an optimal solution for the first model. An example problem solved with the pairwise interchange method indicates that the rule is also fairly efficient for the second model. The proposed rule is compared with other assignment rules of warehouse space such as COI rule, space and popularity.

• Journal of the Korea Society for Simulation
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• v.28 no.3
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• pp.25-40
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• 2019

Today, container terminals are fiercely competing to attract an increasing number of containers. As a way to improve terminal productivity, this study proposes two dispatching rules for yard truck allocation priorities. First, Multi-Attribute Dispatching Rule(MADR) is an allocation method to calculate the weighted sum of multiple factors affecting container terminal productivity and priority them. Especially, the workload of the quay crane was considered one of the factors to reduce the residence time of the ship. Second, Cycling Dispatching Rule(CDR) is the effective way to increase the number of double cycles that directly affect terminal productivity. To identify the effects of combinations of pooling and dispatching, a comparative experiments was performed on 8 scenarios that combined them. A simulation environment has been developed for experiments and the results have demonstrated that the combination of terminal level pooling and Multi-attribute Dispatching could be an excellent combination in KPIs consisting of GCR and delayed departure of ships, etc.

• International Journal of Reliability and Applications
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• v.11 no.1
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• pp.17-22
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• 2010

It is desired to estimate the reliability of a system that has two subsystems connected in series where each subsystem has two components connected in parallel. A batch sequential sampling scheme is introduced. It is shown that the batch sequential sampling scheme is asymptotically optimal as the total number of units goes to infinity. Numerical comparisons indicate that the batch sequential sampling scheme performs better than the balanced sampling scheme and is nearly optimal.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.37-44
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• 2015

A queueing system with 2 parallel workstations is common in the field. Typically, the workstations have different features in terms of the inter arrival times of customers and the service times for the customers. Computer simulation study on the optimal server allocation for parallel heterogeneous queueing systems with fixed number of identical servers is presented in this paper. The queueing system is optimized with respect to minimizing the weighted system time of the customers served by 2 parallel workstations. The system time formula for the M/M/c systems in Kendall's notation is known. Thus, we first compute the optimal allocation for parallel M/M/c systems, comparing the results with those from the computer simulation experiments, and have the same results. The CETI rule is devised through optimizing M/M/c cases, which allocates the servers based on Close or Equal Traffic Intensities between workstations. Traffic intensity is defined as the arrival rate divided by the service rate times the number of servers. The CETI rule is shown to work for M/G/c, G/M/c queueing systems by numerous computer simulation experiments, even if the rule cannot be proven analytically. However, the CETI rule is shown not to work for some of G/G/c systems.