In a two-market genetic algorithm applied to a constrained optimization problem, two ‘markets’ are maintained. One market establishes fitness in terms of the objective functio...
Steven Orla Kimbrough, Ming Lu, David Harlan Wood,...
Approximate symbolic computation problems can be formulated as constrained or unconstrained optimization problems, for example: GCD [3, 8, 12, 13, 23], factorization [5, 10], and ...
Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic "uncertain-butbounded" data perturbations. In this p...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Abstract— Replacement policies for general caching applications and Web caching in particular have been discussed extensively in the literature. Many ad-hoc policies have been pr...