Browsing by Keywords "Problem Solving"

Now showing items 1-6 of 6

    • Circuit partitioning using mean field annealing 

      Bultan, T.; Aykanat, C. (Elsevier, 1995)
      Mean field annealing (MFA) algorithm, proposed for solving combinatorial optimization problems, combines the characteristics of neural networks and simulated annealing. Previous works on MFA resulted with successful mapping ...

    • Comparison of multilevel methods for kronecker-based Markovian representations 

      Buchholz, P.; Dayar T. (Springer, 2004)
      The paper presents a class of numerical methods to compute the stationary distribution of Markov chains (MCs) with large and structured state spaces. A popular way of dealing with large state spaces in Markovian modeling ...

    • Comparison of partitioning techniques for two-level iterative solvers on large, sparse Markov chains 

      Dayar T.; Stewart, W. J. (SIAM, 2000)
      Experimental results for large, sparse Markov chains, especially the ill-conditioned nearly completely decomposable (NCD) ones, are few. We believe there is need for further research in this area, specifically to aid in ...

    • A fast neural-network algorithm for VLSI cell placement 

      Aykanat, C.; Bultan, T.; Haritaoğlu, İ. (Pergamon Press, 1998)
      Cell placement is an important phase of current VLSI circuit design styles such as standard cell, gate array, and Field Programmable Gate Array (FPGA). Although nondeterministic algorithms such as Simulated Annealing (SA) ...

    • Iterative methods based on splittings for stochastic automata networks 

      Uysal, E.; Dayar T. (1998)
      This paper presents iterative methods based on splittings (Jacobi, Gauss-Seidel, Successive Over Relaxation) and their block versions for Stochastic Automata Networks (SANs). These methods prove to be better than the power ...

    • Situated nonmonotonic temporal reasoning with BABY-SIT 

      Tın, E.; Akman, V. (IOS Press, 1997)
      After a review of situation theory and previous attempts at 'computational' situation theory, we present a new programming environment, BABY-SIT, which is based on situation theory. We then demonstrate how problems requiring ...