Optimization by Simulated Annealing
Scott Kirkpatrick, C. D. Gelatt, Mario P. Vecchi
IBM (United States) IBM Research - Thomas J. Watson Research Center Instituto Venezolano de Investigaciones Científicas
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摘要与影响
There is a deep and useful connection between statistical mechanics (the behavior of systems with many degrees of freedom in thermal equilibrium at a finite temperature) and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters). A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. This connection to statistical mechanics exposes new information and provides an unfamiliar perspective on traditional optimization problems and methods.
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计算机 / AIMetaheuristic Optimization Algorithms Research
Theoretical and Computational Physics · Simulation Techniques and Applications
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