• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.159-167
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• 2023

Objective: • To detect black hole and warm hole attacks in wireless sensor networks. • To give a solution for energy depletion and security breach in wireless sensor networks. • To address the security problem using strategic decision support system. Methods: The proposed stackelberg game is used to make the spirited relations between multi leaders and multi followers. In this game, all cluster heads are acts as leaders, whereas agent nodes are acts as followers. The game is initially modeled as Quadratic Programming and also use backtracking search optimization algorithm for getting threshold value to determine the optimal strategies of both defender and attacker. Findings: To find optimal payoffs of multi leaders and multi followers are based on their utility functions. The attacks are easily detected based on some defined rules and optimum results of the game. Finally, the simulations are executed in matlab and the impacts of detection of black hole and warm hole attacks are also presented in this paper. Novelty: The novelty of this study is to considering the stackelberg game with backtracking search optimization algorithm (BSOA). BSOA is based on iterative process which tries to minimize the objective function. Thus we obtain the better optimization results than the earlier approaches.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.337-347
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• 2008

Based on social welfare maximum theory, the optimal scale of power plants entering generation power market being is researched. A static non-cooperative game model for short-term optimization of power plants with different cost is presented. And the equilibrium solutions and the total social welfare are obtained. According to principle of maximum social welfare selection, the optimization model is solved, optimal number of power plants entering the market is determined. The optimization results can not only increase the customer surplus and improve power production efficiency, but also sustain normal profits of power plants and scale economy of power production, and the waste of resource can also be avoided. At last, case results show that the proposed model is efficient.

• Communications of Mathematical Education
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• v.21 no.4
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• pp.597-612
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• 2007

For finding the optimal strategy in Blackout game which was introduced in the homepage of popular movie "Beautiful mind", we have developed and generalized a mathematical proof and an algorithm with a couple of softwares. It did require only the concept of basis and knowledge of basic linear algebra. Mathematical modeling and analysis were given for the square matrix case in(Lee,2004) and we now generalize it to a generalized $m{\times}n$ Blackout game. New proof and algorithm will be given with a visualization.

• Journal of the military operations research society of Korea
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• v.9 no.2
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• pp.61-68
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• 1983

The traditional theories of games are based on an assumption that the payoffs have a single dimension. In reality, any alternative is likely to imply more than one payoff. This paper deals with the game against nature with vector payoffs. The purpose of this paper is to develop methods for finding the practical optimal strategy in the game against nature with vector payoffs. Under the assumption that a prior probability over the stats of nature is given, this paper shows that a practical optimal strategy in this game can be obtained by applying a entropy method in order to assess the payoff weight and by employing the concept of compromise solutions in order to reduce the non-dominated solutions. When subjective payoff weights are unknown as well as known, these methods can be used. A numerical example is given.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.41-48
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• 2011

Recently, the increasing power of distributors has given them the opportunity of introducing private brand (PB) products. Based on the game theory, this study analyzes the decision making of a distributor regarding the optimal pricing and quality strategies for the PB product. By analyzing the game model, it is shown that the pricing mechanism heavily depends not only on the market power of the distributor but on the quality of the PB product. It is also shown that, counter intuitively, as the market power of the distributor increases, the optimal quality of the PB product should be decreased.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3789-3809
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• 2015

In this paper, we deal with the problem of M2M gateways' network selection for different types of M2M traffic in heterogeneous wireless networks. Based on the difference in traffic's quality of service (QoS) requirements, the M2M traffic produced by various applications is mainly classified as two categories: flexible traffic and rigid traffic. Then, game theory is adopted to solve the problem of network-channel selection with the coexistence of flexible and rigid traffic, named as flexible network access (FNA). We prove the formulated discrete game is a potential game. The existence and feasibility of the Nash equilibrium (NE) of the proposed game are also analyzed. Then, an iterative algorithm based on optimal reaction criterion and a distributed algorithm with limited feedback based on learning automata are presented to obtain the NE of the proposed game. In simulations, the proposed iterative algorithm can achieve a near optimal sum utility of whole network with low complexity compared to the exhaustive search. In addition, the simulation results show that our proposed algorithms outperform existing methods in terms of sum utility and load balance.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.57-66
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• 2009

A quest system is one of the important parts in the MMORPG (Massive Multiplayer Online Role Playing Game) contents. Because of its complexity in combining various content components, quest reward design belongs to a complicated work in estimating quest reward levels correctly in the initial development stage. In this paper, we suggest a new quest reward design technique by considering optimal quest play paths. We model a quest reward problem as the TSP (Traveling Salesman Problem) and solve that by adopting genetic algorithms. With our system, game designers easily estimate the optimal quest play path and it can be useful in reducing the trial-errors in the initial quest design process.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.247-255
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• 2004

The majority of real-world problems encountered by engineers involve simultaneous optimization of competing objectives. In this case instead of single optima, there is a set of alternative trade-offs, generally known as Pareto-optimal solutions. The use of evolutionary algorithms Pareto GA, which was first introduced by Goldberg in 1989, has now become a sort of standard in solving Multiobjective Optimization Problems (MOPs). Though this approach was further developed leading to numerous applications, these applications are based on Pareto ranking and employ the use of the fitness sharing function to maintain diversity. Another scheme for solving MOPs has been presented by J. Nash to solve MOPs originated from Game Theory and Economics. Sefrioui introduced the Nash Genetic Algorithm in 1998. This approach combines genetic algorithms with Nash's idea. Another central achievement of Game Theory is the introduction of an Evolutionary Stable Strategy, introduced by Maynard Smith in 1982. In this paper, we will try to find ESS as a solution of MOPs using our game model based co-evolutionary algorithm. First, we will investigate the validity of our co-evolutionary approach to solve MOPs. That is, we will demonstrate how the evolutionary game can be embodied using co-evolutionary algorithms and also confirm whether it can reach the optimal equilibrium point of a MOP. Second, we will evaluate the effectiveness of our approach, comparing it with other methods through rigorous experiments on several MOPs.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.36-47
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• 2009

There exists RFID reader-to reader frequency which can not recognize tag in dense reader nude because the interference causes low SIR. To solve this frequency, the many algorithms based on TDM have been proposed. But the most of existing algorithms not obtain the optimal time allocation but propose heuristic scheduling algorithm. In this paper, we apply game theory which deals with interest between players of game to RFID reader-to reader interference and analyze the time allocation problem of reader based on TDM in terms of cooperative game which the players bind agreements using Nash Bargaining Solution(NBS) and non-cooperative game which the players do not bind agreements using Nash Equilibrium(NE). The applied results show that in dense reader mode, NBS of cooperative game is superior to NE of non-cooperative game and present optimal time allocation in dense reader mode.

• IE interfaces
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• v.23 no.2
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• pp.89-99
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• 2010

Containers are commonly used as an effective and relatively inexpensive method for transporting goods. Unfortunately, there are often imbalances between the number of import and export containers, and some ports have a surplus of empty containers while others have a deficit. The Empty Container Simulation Game was developed to address these problems. The game is a computer role playing simulation that simulates the distribution of empty containers in order to solve empty container imbalances among ports. An optimal solution is obtained by the computer using linear programming (LP). Upon completion of the game, a player's game results are displayed along with the LP solution. The game interface was designed to provide easy access and operation. This game will serve to provide an easy understanding and planning for empty container management.