multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...

clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...

One of the well-known evolutionary algorithms inspired by biological evolution is genetic algorithm (GA) that is employed as a robust and global optimization tool to search for the best or near-optimal solution with the search space. In this paper, this algorithm is used to solve unequalsized machines (or intra-cell) layout problems considering pick-up and drop-off (input/output) points. Such p...

the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

the forecasting of hydrological variables, such as streamflow, plays an important role in water resource planning and management. recently, the development of stochastic models is regarded as a major step for this purpose. streamflow forecasting using the arima model can be conducted when unknown parameters are estimated correctly because parameter estimation is one of the crucial steps in mode...