• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.4
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• pp.199-204
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• 2005

In an electricity market with an imperfect competition, participants make plans of bidding and transaction strategies to maximize their own profits. The market price and the quantity are concerned with the operation reserve as well as the bidding system and demand curves in an electricity market. This paper presents a market model combined by an energy market and an operating reserve market. The competition of the generation producers in the combined market is formulated as a gaming of selecting bid parameters such as intersections and slopes in bid functions. The Nash Equilibrium(NE) is analyzed by using a hi-level optimization; maximization of Social Welfare(SW) and maximization of the producers' profits.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.484-489
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• 2004

When the energy resource available to a particular plant (be it coal, oil, gas, water, or nuclear fuel) is a limiting factor in the operation of the plant, the entire economic dispatch calculation must be done differently. Each economic dispatch calculation must account for what happened before and what will happen in the future. This paper presents a formulation and a solution method for the optimization problem with a fuel constraint in a competitive electricity market. Take-or- Pay (TOP) contract for an energy resource is the typical constraint as a limiting factor. Two approaches are proposed in this paper for modeling the dispatch calculation in a market mechanism. The approaches differ in the subject who considers and inserts the fuel-constraint into its optimization problem. Market operator and each power producer having a TOP contract are assumed as such subjects. The two approaches are compared from the viewpoint of profits. surplus. and social welfare on the basis of Nash Equilibrium.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1705-1711
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• 2017

This paper analyzes the impact of DRA (Demand Response Aggregator) on market power when competing with power generation companies (Gencos) in the electricity market. If congestion occurs in the transmission line, the strategic choice of the power generation company increases exercise of market power. DRA's strategic reduction of power load impacts the strategy of Gencos, which in turn affects the outcome of the load reduction. As the strategy of Gencos changes according to the location of the congested transmission line, the impact on the market depends on the relative location of the congested line and the DRA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2414-2428
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• 2018

In order to solve the problem that the current network security situation assessment methods just focus on the attack behaviors, this paper proposes a kind of network security situation assessment method based on Markov Decision Process and Game theory. The method takes the Markov Game model as the core, and uses the 4 levels data fusion to realize the evaluation of the network security situation. In this process, the Nash equilibrium point of the game is used to determine the impact on the network security. Experiments show that the results of this method are basically consistent with the expert evaluation data. As the method takes full account of the interaction between the attackers and defenders, it is closer to reality, and can accurately assess network security situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.222-236
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• 2019

Wireless content caching in small cell networks has recently been considered as a promising way to alleviate the congestion of the backhaul in emerging heterogenous cellular network. However, how to select files which are cached in SBSs and how to make SBSs work together is an important issue for cooperative cache research for the propose of reducing file download time. In this paper, a Cooperative-Greedy strategy (CGS) among cache-enabled small base stations (SBSs) in small cell network is proposed, in order to minimize the download time of files. This problem is formulated as a Chinese restaurant game.Using this game model, we can configure file caching schemes based on file popularity and the spectrum resources allocated to several adjacent SBSs. Both the existence and uniquencess of a Nash equilibrium are proved. In the theoretical analysis section, SBSs cooperate with each other in order to cache popular files as many as possible near UEs. Simulation results show that the CGS scheme outperforms other schemes in terms of the file-download time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1904-1921
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• 2019

In this paper, we investigate the problem of secure communications in multiple-input-multiple-output interference networks from the perspective of physical layer security. Specifically, the legitimate transmitter-receiver pairs are divided into different categories of active and inactive. To enhance the security performances of active pairs, inactive pairs serve as cooperative jammers and broadcast artificial noises to interfere with the eavesdropper. Besides, active pairs improve their own security by using joint transceivers. The encoding of active pairs and inactive pairs are designed by maximizing the difference of mean-squared errors between active pairs and the eavesdropper. In detail, the transmit precoder matrices of active pairs and inactive pairs are solved according to game theory and linear programming respectively. Experimental results show that the proposed algorithm has fast convergence speed, and the security performances in different scenarios are effectively improved.

• The Pure and Applied Mathematics
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• v.26 no.3
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• pp.133-156
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• 2019

The aim of this paper is to model North Korea and USA relationship since past until now. To this end, we have used game theory. The weakness of the existing models is that they have a static nature and can't analyze the changes of processes, strategies and results. The dynamic system of strategic games of which we have used in this article is a proper method to solve this problem. We have shown that South Korea and China play an important role in resolving the crisis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1817-1836
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• 2020

Network convergence is considered as one of the key solutions to the problem of achieving future high-capacity and reliable communications. This approach overcomes the limitations of separate wireless technologies. Efficient interface selection is one of the most important issues in convergence networks. This paper solves the problem faced by users of selecting the most appropriate interface in the heterogeneous radio-access network (RAN) environment. Our proposed scheme combines a hierarchical evaluation of networks and game theory to solve the network-selection problem. Instead, of considering a fixed weight system while ranking the networks, the proposed scheme considers the service requirements, as well as static and dynamic network attributes. The best network is selected for a particular service request. To establish a hierarchy among the network-evaluation criteria for service requests, an analytical hierarchy process (AHP) is used. To determine the optimum network selection, the network hierarchy is combined with game theory. AHP attains the network hierarchy. The weights of different access networks for a service are calculated. It is performed by combining AHP scores considering user's experienced static network attributes and dynamic radio parameters. This paper provides a strategic game. In this game, the network scores of service requests for various RANs and the user's willingness to pay for these services are used to model a network-versus-user game. The Nash equilibria signify those access networks that are chosen by individual user and result maximum payoff. The examples for the interface selection illustrate the effectiveness of the proposed scheme.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.463-474
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• 2004

Game theory is a method of mathematical analysis developed to study the decision making process. In 1928, Von Neumann mathematically proved that every two-person, zero-sum game with many pure finite strategies for each player is deterministic. In the early 50's, Nash presented another concept as the basis for a generalization of Von Neumann's theorem. Another central achievement of game theory is the introduction of evolutionary game theory, by which agents can play optimal strategies in the absence of rationality. Through the process of Darwinian selection, a population of agents can evolve to an Evolutionary Stable Strategy (ESS) as introduced by Maynard Smith in 1982. Keeping pace with these game theoretical studies, the first computer simulation of coevolution was tried out by Hillis. Moreover, Kauffman proposed the NK model to analyze coevolutionary dynamics between different species. He showed how coevolutionary phenomenon reaches static states and that these states are either Nash equilibrium or ESS in game theory. Since studies concerning coevolutionary phenomenon were initiated, there have been numerous other researchers who have developed coevolutionary algorithms. In this paper we propose a new coevolutionary algorithm named Game theory based Coevolutionary Algorithm (GCEA) and we confirm that this algorithm can be a solution of evolutionary problems by searching the ESS. To evaluate this newly designed approach, we solve several test Multiobjective Optimization Problems (MOPs). From the results of these evaluations, we confirm that evolutionary game can be embodied by the coevolutionary algorithm and analyze the optimization performance of our algorithm by comparing the performance of our algorithm with that of other evolutionary optimization algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.1-8
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• 2019

Network externalities are essentially dynamic in that the value consumers feel about a product is affected by the size of the existing customer base that uses that product. However, existing studies on network externalities analyzed the effects of network externalities in a static way, not dynamic. In this study, unlike previous studies, the impact of network externalities on price competition in a vertically differentiated market is dynamically analyzed. To this end, a two-period duopoly game model was used to reflect the dynamic aspects of network externalities. Based on the game model, the Nash equilibria for price, sales volume, and revenue were derived and numerically analyzed. The results can be summarized as follows. First, if high-end product has strong market power, the high-end product vendor takes almost all benefits of the network externality. Second, when high-end product has strong market power, the low-end product will take over most of the initial sales volume increase. Third, when market power of high-end product is not strong, it can be seen that the effects of network externalities on the high and low-end products are generally proportional to the difference in quality. Lastly, if there exists a strong network externality, it is shown that the presence of low-end product can be more profitable for high-end product vendor. In other words, high-end product vendor has incentive to disclose some technologies for the market entrance of low-end product, even if it has exclusive rights to the technologies. In that case, however, it is shown that the difference in quality should be maintained significantly.