This paper presents novel krill herd (KH) nature-inspired metaheuristics for solving portfolio optimization task. Krill herd algorithm mimics the herding behavior of krill individuals. The objective function for the krill movement is defined by the minimum distances of each individual krill from food and from higher density of the herd. Constrained portfolio optimization problem extends the cla...

Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...

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 paper, we studied the extended Markowitz’s meanvariance portfolio optimization model. We considered the cardinality, quantity, pre-assignment and round lot constraints in the extended model. These four rea...

Abstract. Portfolio theory deals with the question of how to allocate resources among several competing alternatives (stocks, bonds), many of which have an unknown outcome. In this paper we provide an overview of different portfolio models with emphasis on the corresponding optimization problems. For the classical Markowitz mean-variance model we present computational results, applying a dual a...

In this paper, a constrained mean-variance model is constructed for the portfolio optimization problems. The model is a mixed quadratic integer programming problem, and it is too hard to solve by using the traditional optimal algorithms. The purpose of this paper is to use a heuristic algorithm to solve this problem. Combined with the differential evolution strategy, a new hybrid artificial bee...

due to project evaluation complexity and resource constraints, the project portfolio optimization is numerous decision making challenges. hence, many researches have been done to introduce model and methods for portfolio optimization. but most of them have not considered the interaction between projects. considering the interactions between projects increase complexity of portfolio optimization...

In this paper, a cardinality constrained mean-variance model is introduced for the portfolio optimization problems. This model is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. The use of heuristic algorithms in this case is necessary. Some studies have investigated the cardinality constrained mean-variance model using heuristic algorithm. But alm...

A new approach to solve Chance constrained Portfolio Optimization Problems (CPOPs) without using the Monte Carlo simulation is proposed. Specifically, according to Chebyshev inequality, the prediction interval of a stochastic function value included in CPOP is estimated from a set of samples. By using the prediction interval, CPOP is transformed into Lower-bound Portfolio Optimization Problem (...