• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.417-420
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• 2008

We consider the problem of optimizing the performance of a system shared by selfish non-cooperative users. In this problem, small jobs which the users request should be scheduled on a set of shared machines with their speed functions, each of which dependson the amount of jobs allocated on a machine. The performance of the system is measured by the maximum of the completion times when the machines complete the jobs allocated on them. The selfish users can choose a machine on which their jobs are executed, and they choose the fastest machine. But it typically results in suboptimal system performance. The Price of Anarchy(PoA) was introduced as a measure of the performance degradation due to the user's selfish behavior. The PoA is the worst-case ratio of the cost of a Nash equilibrium to the optimal cost. In this paper, we estimate the PoA for the above scheduling problem.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.554-566
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• 2014

An objective of VMS(Variable Message Signs) is to make transportation system effective specifically for driver's path selection. The traffic solutions including a VMS problem can be modeled through Game Theory, however, the majority of the studies can not model various driver's response according to VMS information in game theory. So, this paper tries to analyze a driver's response according to VMS traffic informations through evolutionary game theory. We apply a behavior characteristics of driver to evolutionary game theory, then finds drivers are only accepting in case of the biggest pay-off, and if a traffic flow finds a balance over time, ratio of accepting information is converged as an evolutionary stable state gradually. Consequently, the strategy of the other drivers such as traffic problems can not be predicted accurately. In case, drivers repeat between groups and reasonable judgment by the experience, we expect that VMS can provide strategic information through evolutionary game theory.