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METAHEURISTIC-GUIDED TRUST-TECH METHODS FOR GLOBAL UNCONSTRAINED OPTIMIZATION
METAHEURISTIC-GUIDED TRUST-TECH METHODS FOR GLOBAL UNCONSTRAINED OPTIMIZATION
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机译:用于全局无约束优化的元律指导信托技术方法
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摘要
A method determines a global optimal solution of a system defined by a plurality of nonlinear equations by applying a metaheuristic method to cluster a plurality of search instances into at least one group, selecting a center point and a plurality of top points from the search instances in each group and applying a local method, starting from the center point and top points for each group, to find a local optimal solution for each group in a tier-by-tier manner. Then a TRUST-TECH methodology is applied to each local optimal solution to find a set of tier-1 local optimal solutions, and the TRUST-TECH methodology is applied to each tier-1 local optimal solution to find a set of tier-2 local optimal solutions. A best solution is identified among all the local optimal solutions as the global optimal solution. The heuristic method can be a particle swarm optimization method or a genetic algorithm method.
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