Software testing is an important but complex part of software development life cycle. The optimization of the software testing process is a major challenge, and the generation of the independent test paths remains unsatisfactory. In this paper, we present an approach based on metaheuristic firefly algorithm to generate optimal test paths. In order to optimize the test case paths, we use a modif...

Multi-class classification is one of the major challenges in machine learning and an ongoing research issue. Classification algorithms are generally binary, but they must be extended to multi-class problems for real-world application. more complex than binary classification. In classification, only decision boundaries class known, whereas multiclass several involved. The objective this investig...

In many optimization problems in real world, objective function, design variable or constraints can be changed during time, so optimal value of these problems also can be changed. These kinds of problems are called dynamic. Algorithms which are designed for optimizing in these environments have some principles that distinguish them from algorithms designed in static environment. In this paper, ...

The study of inverse problems applied to radiative transfer has been the subject of numerous studies aiming many applications ranging from medicine to industry formulation for the parameter estimation inverse problems in radiative heat transfer is minimization of an objective function associated with the problem being analyzed. usually inspired by nature behaviors, have been shown effective in ...

Evolutionary algorithms are the choice of many researchers for optimizing machining parameters. Even though evolutionary algorithms are commonly used for solving constrained optimization problems, however in practice sometimes they deliver only insignificant performance. The difficulty with evolutionary algorithms is that they start with random initial population and all its populations become ...

Targets and objects registration and tracking in a sequence of images play an important role in various areas. One of the methods in image registration is feature-based algorithm which is accomplished in two steps. The first step includes finding features of sensed and reference images. In this step, a scale space is used to reduce the sensitivity of detected features to the scale changes. Afterw...

In order to minimize power losses caused by high current and improve the voltage profile in the network distribution, the introduction of dispersed generations also called productions decentralized in distribution network (DG) plays an important role. The installation of DGs directly affects the power requested or purchased. The sizing and placement of DGs in the system must be optimal because ...

Firefly algorithm (FA) is a novel population-based stochastic optimization algorithm and has been shown to yield good performance for solving varieties of optimization problems. Meanwhile, it sustains premature convergence because it is easily to fall into the local optima which may generate a low accuracy of solution or even fail. To overcome this defect, a nonlinear time-varying step strategy...

The bio-inspired optimization techniques have obtained great attention in recent years due to its robustness, simplicity and efficiency to solve complex optimization problems. The firefly Optimization (FA or FFA) algorithm is an optimization method with these features. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be conside...