• Journal of Communications and Networks
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• v.18 no.4
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• pp.629-638
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• 2016

In this paper, we investigate an energy-efficient resource allocation problem in a two-way relay (TWR) network consisting of multiple user pairs and an amplify-and-forward (AF) relay. As the users and relay have individual energy efficiencies (EE), we formulate a multi-objective optimization problem (MOOP). A single-objective optimization problem (SOOP) of the MOOP is introduced using a weighted-sum method, which achieves a single Pareto optimal point of the MOOP. To derive the algorithm for the SOOP, we propose a more tractable equivalent problem using the Karush-Kuhn-Tucker conditions of the SOOP, which guarantees convergence at the local optimal points. The proposed equivalent problem can be efficiently solved by the proposed iterative algorithm. Numerical results demonstrate the effectiveness of the proposed algorithm in achieving the optimal EE in multi-user AF TWR networks.

• Journal of Korea Technology Innovation Society
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• v.17 no.4
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• pp.733-762
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• 2014

The government mandates that national research facilities & equipments through R&D business budget should be registered on the National Science and Technology Information Service (NTIS) for the purpose of the efficient use of the research facilities & equipments. This study is to contribute to the national policies on the efficient management of the research facilities & equipments by recognition methodology with the university's members and analysis of the impact factors of the universities' registration process improvement through the Define level and Measure level of the Six Sigma DAMIC. The survey and interview were conducted on research directors, professors joining university administration, graduate students, researchers, and staffs of A University. The findings are the lack of understanding specific steps and life-cycle management of research facilities & equipments. It is necessary to collect suggestions from universities and pursue policies considered the unique characteristics of the university for advanced operating and maximizing use of university's national research facilities & equipments. Research facilities & equipments enrollment compliance rate and registration accuracy were selected as CTQ-Y through the Six Sigma. 72 potential cause variables were derived through Process Map and C & E Diagram. 13 variables were determined as core potential factors through the X-Y Matrix and Pareto Chart. Research institutions should maximize utilization of research facilities & equipments through deriving a potential variables of the process improvements and designing a detail improvements based on the characteristics of each institutions.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.113-126
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• 1990

With the introduction of the national pension, efficient integration of Korea's four public pension schemes has been discussed. The main point of such discussions is whether to have a progressive scheme or an income-proportional one. Under the assumption of a perfect labor market, it has been proved in the income tax literature that the regressive tax scheme with the 0 % tax rate to the most able person (person earning highest income) is pareto efficient, if there is an incentive problem in the labor supply. In this paper, a life-cycle model with a linear benefit schedule, when there is uncertainty about future earning ability, is studied. It is proved that the second best pension scheme is that having a progressive benefit schedule. This result implies that integration into a progressive pension scheme, like the current national pension, is required not only for efficiency but also for equity.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.137-146
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• 2016

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5A
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• pp.294-304
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• 2003

For an efficient software download in cellular CDMA systems, session admission control based on area (SACA) is presented. In the SACA scheme, the base station only allows mobile terminal to start session when the mobile locates near the base station of a cell. A mobile that is located near cell center can request software download session, but the mobile that is far away from the center can request session only after arriving near the cell center. Session duration time follows exponential and Pareto distribution. Performance is analyzed in terms of handoff rate, mean channel holding time, session blocking probability and handoff forced termination probability. As analysis results, handoff rate between cells in the proposed scheme is reduced to 30 ~ 250 % compared to conventional scheme, according to traffic characteristics such as terminal speed, session duration time and the size of the allowable zone area in a cell for the start of the session. And new session blocking probability slightly decreases to 5 ~ 20 %, but handoff session forced termination probability drastically decreases to 35 ~ 220 %.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1479-1494
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• 2015

Since the Markowitz's mean-variance framework for portfolio analysis, the topic of portfolio optimization has been an important topic in finance. Traditional approaches focus on maximizing the expected return of the portfolio while minimizing its variance, assuming that risky asset returns are normally distributed. The normality assumption however has widely been criticized as actual stock price distributions exhibit much heavier tails as well as asymmetry. To this extent, in this paper we employ the genetic algorithm to find the optimal portfolio under the Value-at-Risk (VaR) constraint, where the tail of risky assets are modeled with the generalized Pareto distribution (GPD), the standard distribution for exceedances in extreme value theory. An empirical study using Korean stock prices shows that the performance of the proposed method is efficient and better than alternative methods.

• Wind and Structures
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• v.32 no.4
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• pp.355-369
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• 2021

Shape optimization of tall buildings is an efficient approach to mitigate wind-induced effects. Several studies have demonstrated the potential of shape modifications to improve the building's aerodynamic properties. On the other hand, it is well-known that the cross-section geometry has a direct impact in the floor area availability and subsequently in the building's profitability. Hence, it is of interest for the designers to find the balance between these two design criteria that may require contradictory design strategies. This study proposes a surrogate-based multi-objective optimization framework to tackle this design problem. Closed-form equations provided by the Eurocode are used to obtain the wind-induced responses for several wind directions, seeking to develop an industry-oriented approach. CFD-based surrogates emulate the aerodynamic response of the building cross-section, using as input parameters the cross-section geometry and the wind angle of attack. The definition of the building's modified plan shapes is done adopting the reduced basis approach, advancing the current strategies currently adopted in aerodynamic optimization of civil engineering structures. The multi-objective optimization problem is solved with both the classical weighted Sum Method and the Weighted Min-Max approach, which enables obtaining the complete Pareto front in both convex and non-convex regions. Two application examples are presented in this study to demonstrate the feasibility of the proposed strategy, which permits the identification of Pareto optima from which the designer can choose the most adequate design balancing profitability and occupant comfort.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.1-7
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• 2009

This paper presents a process routing (PR) algorithm with multiple objectives. PR determines the optimum sequence of operations for transforming a raw material into a completed part within the available machining resources. In any computer aided process planning (CAPP) system, selection of the machining operation sequence is one of the most critical activities for manufacturing a part and for the technical specification in the part drawing. Here, the goal could be to generate the sequence that optimizes production time, production cost, machine utilization or with multiple these criteria. The Pareto Stratum Niche Cubicle (PS NC) GA has been adopted to find the optimum sequence of operations that optimize two conflicting criteria; production cost and production quality. The numerical analysis shows that the proposed PS NC GA is both effective and efficient to the PR problem.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.139-146
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• 2002

The third generation mobile communication needs to provide multimedia service with increased data rates. Thus an efficient allocation of radio and network resources is very important. This paper models the 'burst switching' as an efficient radio resource allocation scheme and the performance is compared to the circuit and packet switching. In burst switching, radio resource is allocated to a call for the duration of data bursts rather than an entire session or a single packet as in the case of circuit and packet switching. After a stream of data burst, if a packet does not arrive during timer2 value ($\tau_{2}$), the channel of physical layer is released and the call stays in suspended state. Again if a packet does not arrive for timerl value ($\tau_{1}$) in the suspended state, the upper layer is also released. Thus the two timer values to minimize the sum of access delay and queuing delay need to be determined. In this paper, we focus on the decision of $\tau_{2}$ which minimizes the access and queueing delay with the assumption that traffic arrivals follow Poison process. The simulation, however, is performed with Pareto distribution which well describes the bursty traffic. The computational results show that the delay and the packet loss probability by the burst switching is dramatically reduced compared to the packet switching.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.959-973
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• 2014

Asset pricing models that account for asymmetric volatility in asset prices have been recently proposed. This article presents an efficient Bayesian method to analyze asset-pricing models. The method is developed by devising a partially collapsed Gibbs sampler that capitalizes on the functional incompatibility of conditional distributions without complicating the updates of model components. The proposed method is illustrated using simulated data and applied to daily S&P 500 data observed from September 1980 to August 2014.