A drawback of robust statistical techniques is the increased computational effort often needed compared to non robust methods. Robust estimators possessing the exact fit property, for example, are NP-hard to compute. This means thatunder the widely believed assumption that the computational...

In this paper, an oppositional backtracking search algorithm (OBSA) is proposed to solve the large scale economic load dispatch (ELD) problem. The main drawback of the conventional backtracking search algorithm (BSA) is that it produces a local optimal solution rather than the global optimal...

Several approaches for solving multi-objective optimization problems entail a form of scalarization of the objectives. This paper proposes a study of different dynamic objectives aggregation methods in the context of evolutionary algorithms. These methods are mainly based on both weighted sum...

Decomposition based algorithms perform well when a suitable set of weights are provided; however determining a good set of weights a priori for real-world problems is usually not straightforward due to a lack of knowledge about the geometry of the problem. This study proposes a novel algorithm...

This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization based on Gaussian Process models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These...

Various preference-based multi-objective evolutionary algorithms have been developed to help a decision-maker search for his/her preferred solutions to multi-objective problems. In most of the existing approaches the decision-maker preferences are formulated either by mathematical expressions...

<Para ID="Par1">We give sufficient conditions which the mutation rate must satisfy for the convergence of the genetic algorithm when that rate is allowed to change throughout iterations. The empirical performance of the algorithm with regards to changes in the mutation parameter is explored via test functions,...</para>

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....

The evolutionary design of time series forecasters is a field that has been explored for several years now. In this paper, a complete design and training of ARMA (Auto-Regressive Moving Average) and ANN (Artificial Neural Networks) models through the use of Evolutionary Computation is presented....

Due to the worldwide energy crisis, research and development activities in the field of renewable energy have been considerably increased in many countries. In Germany, wind energy is becoming particularly important. Although considerable progress has already been achieved, the available...