In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the componen...
A. Ravishankar Rao, Guillermo A. Cecchi, Charles C...
In this paper, we investigate the employment of evolutionary algorithms as a search mechanism in a decision support system for designing chemotherapy schedules. Chemotherapy invol...
In previous optimization-based methods of 3D planar-faced object reconstruction from single 2D line drawings, the missing depths of the vertices of a line drawing (and other parame...
We show that for even quasi-concave objective functions the worst-case distribution, with respect to a family of unimodal distributions, of a stochastic programming problem is a u...
The motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probabi...
A modification of the standard Simulated Annealing (SA) algorithm is presented for finding the global minimum of a continuous multidimensional, multimodal function. We report resu...
A parametric form of tabu-search is proposed for solving mixed integer programming (MIP) problems that creates and solves a series of linear programming (LP) problems embodying br...
Submodular function minimization is a polynomially-solvable combinatorial problem. Unfortunately the best known general-purpose algorithms have high-order polynomial time complexi...
The purpose of this paper is to apply the scatter search methodology to general classes of binary problems. We focus on optimization problems for which the solutions are represent...
Background: Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For examp...
Erwin P. Gianchandani, Matthew A. Oberhardt, Antho...