Optimization with neural networks trained by evolutionary algorithms
M.I. Velazco, Christiano Lyra · 2003
Multilayer neural networks are trained to solve optimization problems. Genetic algorithms are adopted to "evolve" weights, unveiling new points in the definition domain. As the evolution goes on, better points are found, driving the process to optimality. Case studies with convex and nonconvex problems illustrate the approach.