METAHEURISTIC-GUIDED TRUST-TECH METHODS FOR GLOBAL UNCONSTRAINED OPTIMIZATION

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.

主权项

1. A method of determining a global optimal solution of a system defined by a plurality of nonlinear equations, the method comprising the steps of:
a) a computer applying a metaheuristic method to cluster a plurality of search instances into at least one promising region that may contain the global optimal solution; b) the computer selecting a center point and a plurality of top points from the search instances in each promising region; c) the computer applying a local method starting from the center point and top points for each promising region to find a local optimal solution for each promising region in a tier-by-tier manner; d) the computer applying a TRUST-TECH methodology to each local optimal solution to find a set of tier-1 optimal solutions; and e) the computer determining a best solution among the local optimal solutions and the tier-1 optimal solutions and identifying the best solution as the global optimal solution.