On Development of a Generalized Visual Stochastic Optimizer

Abstract

Visual optimization is a very interesting topic to the application users for many purposes. It enables the user with an interactive platform where, by varying different parameter settings, one can customize a solution. Several attempts of developing generalized evolutionary optimizers are found in literature. In this paper, we have tried to develop a generalized visual platform for stochastic optimization algorithms that encompass both single objective and multi objective problems.