This paper reproduces the performance of a geometric average Spot Energy Index by investing only in a subset of stocks from the Dow Jones Composite Average, the FTSE 100 and Bovespa Composite indexes, and in two pools that include only energy-sector stocks from the US and the UK respectively. Daily data are used and the index-tracking problem for passive investment is addressed with two evoluti...

The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Multi-objective Optimization Problems (MOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto-optimal solutions in a single run. Differential Evolution (DE) is an EA that was developed to handle optimization problems over continuous ...

this paper focuses on multi-objective designing of multi-machine thyristor controlled series compensator (tcsc) using strength pareto evolutionary algorithm (spea). the tcsc parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a spea ...

The use of evolutionary strategies (ESs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, ESs offer a means to find a set of Pareto-optimal solutions in a single run. Differential Evolution (DE) is an ES that was developed to handle optimization problems over continuous domains. Th...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...

A Direct method of computing mixed form Nash equilibria of a normal form game by using a simple evolutionary algorithm is proposed. The Direct Evolutionary Search algorithm (DES) uses a generative relation for Nash equilibria with binary tournament selection and uniform mutation. Numerical experiments are used to illustrate the efficiency of the method.

The application of Evolutionary algorithms (EAs) for multi-objective problems (MOPs) has been receiving a growing interest since 1980s. Among the large amount of literature in this area, differential evolution (DE) for MOPs is widely investigated and has shown several advantages over other EAs. However, due to the inherent characteristics of MOPs, plain DE cannot be directly applied for MOPs bu...

In the present paper, a method for building a map of an unknown environment (SLAM) derived from the ICP algorithm using point-to-point metric is proposed. The polarscan matching technology is used for estimation of the robot location change between two scans in sequence estimate the correct position of the robot. Since map building is fairly timeconsuming, the algorithm of differential evolutio...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

In this participation are discussed principles of bioinformatics, datamining, evolutionary computing and its mutual intersection. Datamining by means of selected evolutionary techniques are discussed with attention on protein structure, segmentation and state of art on the field of evolutionary algorithms use. Basic principles and terminology of evolutionary algorithms, as well as two evolution...