Multi-strategy System and Program Design for Multimodal Optimization
碩士 === 國立臺灣科技大學 === 機械工程研究所 === 84 === Simulated annealing belongs to a category of combinatorial global optimization methods. The use of multiple-state simulated annealing provides the ability of locating the global optimum as well as other local optima...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
1996
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| Online Access: | http://ndltd.ncl.edu.tw/handle/74058416100678084946 |
| Summary: | 碩士 === 國立臺灣科技大學 === 機械工程研究所 === 84 === Simulated annealing belongs to a category of combinatorial
global optimization methods. The use of multiple-state
simulated annealing provides the ability of locating the global
optimum as well as other local optima existing in the design
space. The primary drawback of simulated annealing is the slow
convergence rate to an accurate optimum. Crystallization
strategy can be used to predict near-optimum designs from a
number of designs already evaluated and start subsequent local
searches from those identified near-optimum designs.
Traditional gradient-based nonlinear programming methods can
efficiently lead to an optimum with no guarantee that the
optimum is a global optimum. This thesis developed a multiple-
strategy optimization system and program to combine strengths
of all three optimization methods and provide a number
approaches to search the global and other local optima in a
multimodal optimization problem with high efficiency.
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