Yousaf Shad Muhammad

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Massively Multi-player Online Games have emerged as a most intensive data application nowadays. Being massively used by simultaneously game players around the world. This data require high level of performance, fault tolerance and scalability. Distributed databases are one of the option we got for this kind of systems. The goal is to give game players a(More)
We consider the problem of multivariate multi-objective allocation where no or limited information is available within the stratum variance. Results show that a game theoretic approach (based on weighted goal programming) can be applied to sample size allocation problems. We use simulation technique to determine payoff matrix and to solve a minimax game.
In this article, we propose compromise allocations for multivariate stratified random sampling using the auxiliary attributes under non-response. We modified extended lexicographic goal programming technique and compared it with fuzzy goal programming and value function technique. We addressed the problem of compromise allocation when the auxiliary(More)
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