• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.113-127
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• 2014

The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.125-136
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• 2012

Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.1
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• pp.145-149
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• 2014

I consider the optimal consumption and portfolio selection problem with nonnegative wealth constraints using the dynamic programming approach. I use the constant relative risk aversion (CRRA) utility function and disutility to derive the closed-form solutions.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1845-1850
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• 2003

The underground utility tunnels are important facility as a mainstay of country because of communication developments. The communication and electrical duct banks as well as various utility lines for urban life are installed in the underground utility tunnel systems. If a fire breaks out in this life-line tunnel, the function of the city will be discontinued and the huge damages are occurred. In order to improve the safety of life-line tunnel systems and the fire detection, the behaviors of the fire-induced smoke flow and temperature distribution are investigated. In this study we assumed that the fire is occurred at the contact or connection points of cable. Numerical calculations are carried out using different velocity of ventilation in utility tunnel. The fire source is modeled as a volumetric heat source. Three-dimensional flow and thermal characteristics in the underground tunnel are solved by means of FVM (Finite Volume Method) using SIMPLE algorithm and standard ${\kappa}-{\varepsilon}$ model for Reynolds stress terms. The numerical results of the fire-induced flow characteristics in an underground utility tunnel with different velocity of ventilation are graphically prepared and discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4188-4206
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• 2016

Power control is widely used to reduce co-channel interference in wireless networks and guarantee the signal-to-interference plus noise ratio (SINR) of ongoing connections. This technique is also effective for wireless body area networks (WBANs). Although achieving satisfactory SINR is important for WBAN users, they may not be willing to achieve it at arbitrarily high power levels since power is a scarce resource in WBANs. Besides, for WBANs with different purposes, the QoS requirements and concern about the power consumption may be different. This motivates us to formulate the power control problem using the concepts from microeconomics and game theory. In this paper, the QoS objective is viewed as a utility function, which represents the degree of user satisfaction, while the power consumption is viewed as a cost function. The power control problem consequently becomes a non-cooperative multiplayer game, in which each player tries to maximize its net utility, i.e., the utility minus the cost. Within this framework, we investigate the Nash equilibrium existence and uniqueness in the game and derive the best response solution to reach the Nash equilibrium. To obtain the optimal transmission power in a distributed way, we further propose a utility-based and QoS-aware power control algorithm (UQoS-PCA). Tunable cost coefficient in UQoS-PCA enables this scheme to be flexible to satisfy diverse service requirements. Simulation results show the convergence and effectiveness of the proposed scheme as well as improvements over existing algorithm.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.57-59
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• 2001

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model has been studied, proposed, and applied. Among those models, power pool is more popular than others. This paper assumes the power pool market structure having competitive generation sector and a new method is presented to build bidding strategy in that market. The utilities participating in the market have the perfect information on their cost and price functions, but they don't know the strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price function into discrete step function. An utility knows only his own strategy, so he estimates the other's strategy using stochastic methods. For considering these conditions, we introduce the Bayesian rules and noncooperative game theory concepts. Also additional assumptions are included for simplification of solving process. Each utility builds the strategy to maximize his own expected profit function using noncooperative Bayesian game. A numerical example is given in case study to show essential features of this approach.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.882-889
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• 2010

This paper presents a method of finding the optimal operating point minimizing a given objective function with 3 phase power flow equations and operational constraints, called 3 phase optimal power flow (3POPF). 3 phase optimal power flow can provide operation and control strategies for the distribution systems with distributed generation assets, which might be frequently in unbalanced conditions assuming that high penetration rate of renewable energy sources in the systems. As the solution technique for 3POPF, this paper adopts a simulation-based method of particle swarm optimization (PSO). In the PSO based 3POPF, a utility function needs to be defined for evaluation of the degree in operational improvement of each particle's current position. To evaluate the utility function, in this paper, NR-based 3 phase power flow algorithm was developed which can deal with looped distributed generation systems. In this paper, illustrative examples with a 5-bus and a modified IEEE 37-bus test systems are given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3566-3582
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• 2019

In intelligent warehouse picking system, the allocation of tasks has an important influence on the efficiency of the whole system because of the large number of robots and orders. The paper proposes a method to solve the task allocation problem that multi-robot task allocation problem is transformed into transportation problem to find a collision-free task allocation scheme and then improve the capability of task processing. The task time window and the power consumption of multi-robot (driving distance) are regarded as the utility function and the maximized utility function is the objective function. Then an integer programming formulation is constructed considering the number of task assignment on an agent according to their battery consumption restriction. The problem of task allocation is solved by table working method. Finally, simulation modeling of the methods based on table working method is carried out. Results show that the method has good performance and can improve the efficiency of the task execution.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.386-392
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• 1997

Recently, according to developing industry and life style, power consumption have been increased year after year. Currently these much power demand from power consumer is weakening the allowable power reserve margin in summer. As one of the remedies about this problem, the small scale utility interactive photovoltaic system(UIPVS) is considered for auxiliary power source. For this system one of problems to be solved technically, system operating power factor. Generally in case of small scale system, system is operated in unity power factor. But this unity power factor operating mode decrease power factor viewed from utility because UIPVS supply active power to utility. Therefore this paper propose UIPVS with power factor correcting function and this system is analyzed.