3 years ago

Doshisha University (Private)

Doshisha University (Private)

Grids A grid refers to

Grids A grid refers to the systems and technologies to unify computational resources, human capital, and other resources that exist distributed in remote locations in order to use them as a single system. Through the development of grid middleware that can integrate multiple computers, applications, and services located distributed on a wide area network, the Grid Group is developing systems that can solve large-scale, complicated optimization problems such as structural optimal design. We are also participating in representative grid test beds such as ApGrid and OBIGrid and by providing large-scale PC clusters, we are contributing to grid research inside Japan and overseas. Simulated Annealing Simulated Annealing (SA) is an optimization method that simulates annealing in an attempt to obtain a superior crystal structure by gradually cooling materials melted at high temperatures. In the SA Group, we are improving SA with parallelization/decentralization, other optimization methods, and hybridization with evolutionary computation. SA is also applicable to actual optimization problems represented by LSI wiring design. In the SA Group, we are applying SA to actual optimization problems such as applying SA to the optimum design of Gain Flattening Filters (GFF)*. * A filter that has a function to smooth out variations in the amplification amount that differs according the light's wavelength

Genetic Algorithms Genetic algorithms are optimization algorithms that simulate the process of biological evolution. By using the target problem's candidate solutions to resemble individual organisms and applying operators such as genetic cross over and mutation/natural selection to them, the candidate solution evolves and we can obtain the optimal solution. We are also investigating parallel models for genetic algorithms and conducting broad research on implementing genetic algorithms on PC clusters. Interactive Genetic Algorithms In the Interactive Genetic Algorithms Group, we are conducting research using Interactive Genetic Algorithms (IGA), one of the interactive evolutionary computing methods, as a technique for optimization based on human sensibility. We are proposing sign sound generation systems using IGA to create sign sounds used in household appliances and proposing Global Asynchronous Distributed Interactive Genetic Algorithms (GADIGA) as a technique to expand IGA into a massive participation model.

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