in this paper an approach based on evolutionary algorithms to find pareto optimal pair of state and control for multi-objective optimal control problems (moocp)'s is introduced‎. ‎in this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

finding an optimal path for a robot in a soccer field involves different parameters such as the positions of the robot, positions of the obstacles, etc. due to simplicity and smoothness of ferguson spline, it has been employed for path planning between arbitrary points on the field in many research teams. in order to optimize the parameters of ferguson spline some evolutionary or intelligent al...

In the recent years, the optimization techniques using evolutionary algorithms have been widely used to solve electromagnetic problems. These algorithms use thinning the antenna arrays with the aim of reducing the complexity and thus achieving the optimal solution and decreasing the side lobe level. To obtain the optimal solution, thinning is performed by removing some elements in an array thro...

the main purpose in this paper, to express strong algorithmic optimization in their ability to detect expression target of sar that use in aircraft, plane and satellites to observe the target on the ground. for this purpose,the sar technology and its applications are introduced. previous algorithms used in this field with poor diagnosis and appropriate speed is low, like means and fuzzy and pso...

the multivariate exponentially weighted moving average (mewma) control chart is one of the best statistical control chart that are usually used to detect simultaneous small deviations on the mean of more than one cross-correlated quality characteristics. the economic design of mewma control charts involves solving a combinatorial optimization model that is composed of a nonlinear cost function ...

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...