A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems

A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems

Global optimization methods play an important role to solve many real-world problems. Flower pollination algorithm (FP) is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new hybrid optimization method called hybrid flower pollination algorithm (FPPSO) is proposed. The method combines the standard flower pollination algorithm (FP) with the par...

a new hybrid flower pollination algorithm for solving constrained global optimization problems

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...

A Penalty-free Method for Equality Constrained Optimization

A penalty-free method is introduced for solving nonlinear programming with nonlinear equality constraints. This method does not use any penalty function, nor a filter. It uses trust region technique to compute trial steps. By comparing the measures of feasibility and optimality, the algorithm either tries to reduce the value of objective function by solving a normal subproblem and a tangential ...

A Hybrid Algorithm for Global Optimization Problems

We propose a hybrid algorithm for solving global optimization problems that is based on the coupling of the Simultaneous Perturbation Stochastic Approximation (SPSA) and Newton-Krylov Interior-Point (NKIP) methods via a surrogate model. There exist verified algorithms for finding approximate global solutions, but our technique will further guarantee that such solutions satisfy physical bounds o...

Adaptive Penalty Methods for Genetic Optimization of Constrained Combinatorial Problems