in this paper, trajectory generation for the 4 dof arm of surena iii humanoid robot with the purpose of optimizing energy and avoiding a moving obstacle is presented. for this purpose, first, kinematic equations for a seven dof manipulator are derived. then, using the lagrange method, an explicit dynamics model for the arm is developed. in the next step, in order to generate the desired traject...

in this paper, genetic algorithms (gas) are employed to control simultaneous linear systems in both state and output feedback. first, the similarity transformation is applied to obtain parameterized controllers. this requires solution of a system of equations and also some non-linear inequalities. gas are used to solve these equations and inequalities. therefore, the paper presents an analytica...

optimization is an important methodology for activities in planning and design. the transportation designers are able to introduce better projects when they can save time and cost of travel for project by optimization methods. most of the optimization problems in engineering are more complicated than they can be solved by custom optimization methods. the most common and available methods are he...

in recent years, the trend in solving optimization problems has been directed toward using heuristic algorithms such as neural networks, genetic and ant colony algorithms. the main reason for this trend can be attributed to the fact that these algorithms can be efficiently adjusted to the specific search space to which they are applied and consequently they can be used for many optimization pro...

The performance of different mutation operators is usually evaluated in conjunction with specific parameter settings of genetic algorithms and target problems. Most studies focus on the classical genetic algorithm with different parameters or on solving unconstrained combinatorial optimization problems such as the traveling salesman problems. In this paper, a subpopulation-based genetic algorit...

The use of genetic algorithms for solving aerospace control system design and optimization problems is investigated. A modified genetic algorithm based on floating point representation of the chromosome and appropriate genetic operators is developed and used to design controller gains for an autonomous airvehicle. The controller design problem is formulated along a classical pattern with requir...

We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that operate on bits of a string and genetic grouping algorithms that operate on subsets of a set. It employs a segment fair crossover operation. For evaluating segmentations, we define similarity adjace...

We describe a genetic segmentation algorithm for video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that operate on bits of a string and genetic grouping algorithms that operate on subsets of a set. For evaluating segmentations, we define similarity adjacency functions, which are extremely expensive to optimize with traditio...

This paper is a survey of genetic algorithms for t h e traveling salesman problem. Genetic algorithms are randomized search techniques that simulate some of the processes observed i n natural evolution. In this paper, a simple genetic algorithm is introduced, and various extensions are presented to solve t h e traveling salesman problem. Computational results are also repor ted for both random ...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...