Portfolio optimization has been studied extensively by researchers in computer science and
finance, with new and novel work frequently published. Traditional methods, such as …

The coinciding development of multiobjective evolutionary algorithms (MOEAs) and the
emergence of complex problem formulation in the finance and economics areas has led to a …

Portfolio optimization involves the optimal assignment of limited capital to different available
financial assets to achieve a reasonable trade-off between profit and risk objectives. In this …

We formulate the portfolio selection as a tri-objective optimization problem so as to find
tradeoffs between risk, return and the number of securities in the portfolio. Furthermore …

Recent work has been devoted to study the use of multiobjective evolutionary algorithms
(MOEAs) in stock portfolio optimization, within a common mean-variance framework. This …

This paper investigates the ability of Multiobjective Evolutionary Algorithms (MOEAs),
namely the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based …

Stock traders consider several factors or objectives in making decisions. Moreover, they
differ in the importance they attach to each of these objectives. This requires a tool that can …

The Portfolio selection problem is a relevant problem arising in finance and economics.
Some practical formulations of the problem include various kinds of nonlinear constraints …

This paper addresses evolutionary multi-objective portfolio optimization in the practical
context by incorporating realistic constraints into the problem model and preference criterion …

Portfolio selection is a problem arising in finance and economics. While its basic
formulations can be efficiently solved using linear or quadratic programming, its more …