On upper semicontinuity of global minima in constrained optimization problems

Certified Global Minima for a Benchmark of Difficult Optimization Problems

We provide the global optimization community with new optimality proofs for 6 deceptive benchmark functions (5 bound-constrained functions and one nonlinearly constrained problem). These highly multimodal nonlinear test problems are among the most challenging benchmark functions for global optimization solvers; some have not been solved even with approximate methods. The global optima that we r...

Global optimization of robust chance constrained problems

We propose a stochastic algorithm for the global optimization of chance constrained problems. We assume that the probability measure with which the constraints are evaluated is known only through its moments. The algorithm proceeds in two phases. In the first phase the probability distribution is (coarsely) discretized and solved to global optimality using a stochastic algorithm. We only assume...

Topographical Global Optimization for Constrained Problems

In topographical global optimization a sample of points that superuniformly cover the region of interest, A, is used in combination with the function evaluations in these points to obtain a topographical graph of A from which candidate points are easily extracted for local minimizations. This paper discusses some of the problems in obtaining such a cover and presents some solutions. These solut...

Global optimization algorithms for bound constrained 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...