projects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. an integer programming model is formulated for the project portfolio selection and scheduling.two heuristic algorithms, genetic algorithm (ga) and simulated annealing (sa), are presented to solve the problem. results of cal...

In Systems Biology, system identification, which infers regulatory network in genetic system and metabolic pathways using experimentally observed time-course data, is one of the hottest issues. The efficient numerical optimization algorithm to estimate more than 100 real-coded parameters should be developed for this purpose. New real-coded genetic algorithm (RCGA), the combination of AREX (adap...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

The transitional flight of tail-sitter aircraft is a challenging problem because the flight includes a wide operating range with nonlinearity and at low speed approaches the stall. In order to solve this problem, a robust autopilot design method using a variable environment genetic algorithm (VE-GA) is proposed. VE-GA is a new robust optimization method based on a real coded genetic algorithm (...

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...

in this paper, we have proposed a new algorithm which combines pso and ga in such a way that the new algorithm is more effective and efficient.the particle swarm optimization (pso) algorithm has shown rapid convergence during the initial stages of a global search but around global optimum, the search process will become very slow. on the other hand, genetic algorithm is very sensitive to the in...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

This paper presents a real-coded estimation distribution algorithm (EDA) inspired to the extended compact genetic algorithm (ECGA) and the real-coded Bayesian Optimization Algorithm (rBOA). Like ECGA, the proposed algorithm partitions the problem variables into a set of clusters that are manipulated as independent variables and estimates the population distribution using marginal product models...

This paper presents a solution to Optimal Unit commitment (UC) of thermal units based on a evolutionary algorithm known as Genetic algorithm (GA). In this proposed method of GA for the UC problem, the scheduling variables are coded as integers, so that the minimum up/down time constraints can be handled directly. To verify the performance of the proposed algorithm, it is applied to systems with...