One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Aggregate measures summarizing subsets of data are valuable in exploratory analysis and decision support, especially when dependent aggregations can be easily specified and compute...
Lei Chen 0003, Christopher Olston, Raghu Ramakrish...
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
—We consider constrained minimization of a sum of convex functions over a convex and compact set, when each component function is known only to a specific agent in a timevarying...
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. I...