• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.66-71
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• 1988

Let B be present value of some sequence. This paper concerns the maximization of the expected utility of the present value B when the utility function is exponential.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.57-64
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• 2019

We consider the D2D sum utility maximization in the cellular system. D2D links reuse the uplink resource of cellular system. This reuse may cause severe interference to cellular users. To protect the cellular users, interference limit from the D2D links is required. In this setting, D2D sum utility maximization problem is investigated. Each D2D link has limited transmit power budget. Because optimum solution may require global information between links and computational complexity, we propose the distributed algorithm which only require the local information from each D2D link and simple broadcasting. Simulation results are provided to verify the performance of the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.79-85
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• 2019

We investigate the D2D utility maximization in the cellular system. We focus on the non cooperative game theoretic approach to maximize the individual utility. Cellular system's perspective, interference from the D2D links must be limited to protect the cellular users. To accommodate this interference issue, utility function is first defined to control the individual D2D user's transmit power. More specifically, utility function includes the pricing which limits the individual D2D user's transmit power. Then, non cooperative power game is formulated to maximize the individual utility. Distributed algorithm is proposed to maximize the individual utility, while limiting the interference. Convergence of the proposed distributed algorithm is verified through computer simulation. Also the effect of pricing factor to SIR and interference is provided to show the performance of the proposed distributed algorithm.

• Korean Management Science Review
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• v.28 no.1
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• pp.159-167
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• 2011

The theory of random utility maximization (RUM) defines the probability of an alternative being chosen as the probability of its utility being perceived as higher than those of all the other competing alternatives in the choice set (Marschak 1960). According to this theory, consumers perceive the utility of an alternative not as a constant but as a probability distribution. Over the last two decades, there have been an increasing number of studies on the effect of utility variance on choice probability. The common result of the previous studies is that as the utility variance increases, the effect of the mean value of the utility (the deterministic component of the utility) on choice probability is reduced. This study provides a theoretical investigation on the effect of utility variance on choice probability without any assumptions on the specific forms of probability distributions. This study suggests that without assumptions of the probability distribution functions, firms cannot apply the marketing strategy of maximizing choice probability (or market share), but can only adopt the strategy of maximizing the minimum or maximum value of the expected choice probability. This study applies the Chebyshef inequality and shows how the changes in utility variances affect the maximum of minimum of choice probabilities and provides managerial implications.

• Journal of applied mathematics & informatics
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• v.36 no.3_4
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• pp.301-306
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• 2018

I obtain the optimal portfolio and consumption strategies of an investor who have a Cobb-Douglas utility function. And I assume that there is negative wealth constraints. This constraints mean that the investor can borrow partially against her future labor income.

• East Asian mathematical journal
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• v.34 no.3
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• pp.331-338
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• 2018

We investigate the optimal consumption and portfolio strategies of an agent who has a constant elasticity of substitution (CES) utility function under the negative wealth constraint. We use the martingale method to derive the closed-form solution, and we give some numerical implications.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.89-90
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• 2019

본 논문에서는 D2D 단말이 셀룰라 시스템의 상향링크 자원을 재사용하는 환경에서 D2D 단말들의 효용함수 극대화 방안을 제안한다. 기존 셀룰라 단말의 간섭영향을 고려하여 기지국 수신단 총 간섭량을 제한하고, D2D 송신단 전송전력량을 제한한다. D2D 단말들의 효용 극대화를 위해서는 모든 링크간의 채널 정보를 요구하므로, 부분적인 링크 채널 정보만을 필요로 하는 분산적 알고리즘을 제안하도록 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.219-221
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• 2012

The concave utility in the Network Utility Maximization (NUM) problem is only suitable for elastic flows. In networks with multiclass traffic, the utility can be concave, linear, step or sigmoidal. Hence, the basic NUM becomes a nonconvex optimization problem. The current approach utilizes the standard dual-based decomposition method. It does not converge in case of scarce resource. In this paper, we propose an algorithm that always converges to a local optimal solution to the nonconvex NUM after solving a series of convex approximation problems. Our techniques can be applied to any log-concave utilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.193-214
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• 2017

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5B
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• pp.295-303
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• 2007

An algorithm is proposed to seek a local optimal solution of the network utility maximization problem in a wireless mesh network, where the architecture being considered is an infrastructure/backbone wireless mesh network. The objective is to achieve proportional fairness amongst the end-to-end flows in wireless mesh networks. In order to establish the communication constraints of the flow rates in the network utility maximization problem, we have presented necessary and sufficient conditions for the achievability of the flow rates. Since wireless mesh networks are generally considered as a type of ad hoc networks, similarly as in wireless multi-hop network, the network utility maximization problem in wireless mesh network is a nonlinear nonconvex programming problem. Besides, the gateway/bridge functionalities in mesh routers enable the integration of wireless mesh networks with various existing wireless networks. Thus, the rate optimization problem in wireless mesh networks is more complex than in wireless multi-hop networks.