Title and abstract for

Physical Optimization and Physical Computation -- CPS713 update from November 1992 Talk at Houston Keck Symposium

Given by Geoffrey C. Fox at CPSP713 Case studies in Computational Science on Spring Semester 1996. Foils prepared 15 March 1996
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Physical Optimization applies a set of Optimization (minimization) methods motivated by physical processes to general optimization problems
These include simulated annealing, neural networks, deterministic annealing, simulated tempering and genetic algorithms
We look at general TSP, clustering in physical spaces, track finding, navigation, school class scheduling, Random field Ising Models and data decomposition and other computing optimization problems
We discuss when methods such as neural networks are effective
Northeast Parallel Architectures Center, Syracuse University, npac@npac.syr.edu

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