In metaheuristic optimization, understanding the relationship between problems and algorithms is important but non-trivial. There has been a growing interest in the literature on techniques for analysing problems, however previous work has mainly been developed for discrete problems. In this paper, we develop a novel framework for characterising continuous optimization problems based on the con...

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 globa...

Wine consumers’ willingness (wine neophilia) or reluctance neophobia) to try new wines represent, respectively, an opportunity barrier for product innovation and market development in the wine industry. Here, we first sought validate optimize Neophobia Scale (WNS) a large sample of 1269 Canadian consumers. Both exploratory confirmatory factor analyses showed that seven-item scale was optimal. T...

We present a new multiscale contour tting process which combines information about the image and the contour of the object at di erent levels of scale. The algorithm is based on energy minimizing deformable models but avoids some of the problems associated with these models. The segmentation algorithm starts by constructing a linear scale-space of an image through convolution of the original im...