Efficient Adaptive Global Optimization for 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...

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...

Adaptive memory programming for constrained global optimization

The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multistart procedures discussed in Ugray et al. (2007) are the most effective. We present some new multistart methods based on the framework of adaptive...

Global optimization algorithms for bound constrained problems

Constrained Efficient Global Optimization for Pultrusion Process

Composite materials, as the name indicates, are composed of different materials which yield superior performance as compared to individual components. Pultrusion is one of the most costeffective manufacturing techniques for producing fiber reinforced composites with constant cross sectional profiles. This obviously makes it more attractive for both researchers and practitioners to investigate t...