The key to multi-robot exploration is how to select appropriate targets for robots to avoid collision and overlap. However, the distribution of targets for multiple robots is an NP hard problem. This paper presents a multirobot cooperative exploration strategy based on the immune genetic algorithm. With its random global searching and parallel processing, genetic algorithm is applied for multi-...

A novel clinical decision support system is proposed in this paper for evaluating the fetal well-being from the cardiotocogram (CTG) dataset through an Improved Adaptive Genetic Algorithm (IAGA) and Extreme Learning Machine (ELM). IAGA employs a new scaling technique (called sigma scaling) to avoid premature convergence and applies adaptive crossover and mutation techniques with masking concept...

Using a dynamic systems model for the Simple Genetic Algorithm due to Vose, we analyze the fixed point behavior of the model without crossover applied to functions of unitation. Unitation functions are simplified fitness functions that reduce the search space into a smaller number of equivalence classes. This reduction allows easier computation of fixed points. The effect of model fixed points ...

Many studies are performed by researchers about Shell and Tube Heat Exchanger but the Multi-Objective Big Bang-Big Crunch algorithm (MOBBA) technique has never been used in such studies. This paper presents application of Thermal-Economic Multi-Objective Optimization of Shell and Tube Heat Exchanger Using MOBBA. For optimal design of a shell and tube heat exchanger, it was first thermally model...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Determining the optimal build directions is one of the most critical factors in RP processes because it affects on the build time, support structure, surface quality as well as the cost. The previous methods could handle simple parts or limited objective functions. Moreover the methods with multiple objective functions, had abstracted them into a single fitness function in which the characteris...

in this paper, the quantitative structure activity-relationship (qsar) of the ccr2b receptor inhibitors was scrutinized. firstly, the molecular descriptors were calculated using the dragon package. then, the stepwise multiple linear regressions (sw-mlr) and the genetic algorithm multiple linear regressions (ga-mlr) variable selection methods were subsequently employed to select and implement th...

a robust and reliable quantitative structure-property relationship (qspr) study was established to forecast the melting points (mps)  of a diverse and long set including 250 drug-like compounds. based on the calculated descriptors by dragon software package, to detect homogeneities and to split the whole dataset into training and test sets, a principal component analysis (pca) approach was used...

To reduce reconstruction errors during keyframe extraction and to control the optimal compression ratio, this study proposes a method for keyframe extraction from human motion capture data based on a multiple population genetic algorithm. The fitness function is defined to meet the goals of minimal reconstruction errors and the optimal compression rate, where multiple initial populations are su...

Genetic and evolutionary algorithms have been increasingly applied to solve complex, large scale search problems with mixed success. Competent genetic algorithms have been proposed to solve hard problems quickly, reliably and accurately. They have rendered problems that were difficult to solve by the earlier GAs to be solvable, requiring only a subquadratic number of function evaluations. To fa...