RPCGB Method for Large-Scale Global Optimization Problems

In this paper, we propose a new approach for optimizing large-scale non-convex differentiable function subject to linear equality constraints. The proposed method, RPCGB (random perturbation of the conditional gradient method with bisection algorithm), computes search direction by gradient, and an optimal line is found algorithm, which results in decrease cost function. designed guarantee global convergence algorithm. An implementation testing are given, numerical problems that demonstrate its efficiency.