Abstract
This paper proposes a genetic algorithm to generate trajectories for robotic manipulators. The objective is to minimize the ripple in the trajectory time evolution and to minimize the actuator energy requirements without colliding with any obstacles in the workspace, The article presents the results for several redundant and hyper-redundant manipulators.

Abstract
This paper presents two evolutionary schemes and a swarm intelligence algorithm for the design of combinational logic circuits. A Genetic and a Memetic schemes as the evolutionary algorithms. The Particle Swarm Optimization as the swarm algorithm. The fitness function used in these three algorithms is sequential, that is, divided in two parts. The first part of the fitness function f(1) evaluates the circuit functionality, while the second part f(2) deals with the circuit complexity. The experiments consist in applying the algorithms in the design of two arithmetic circuits: the one-bit full adder and the one-bit full subtractor. We also present a scalability analysis using the parity checker family of circuits.

Abstract
This paper proposes a method, based on a genetic algorithm, to generate smoth manipulator trajectories in a multi-objective perspective. The method uses terms proportional to the integral of the squared displacements in order to eliminate the jerk movement. In this work, the algorithm, based on NSGA-II and maximin sorting schemes, considers manipulators of two, three and four rotational axis (2R, 3R, 4R). The efficiency of the algorithm is evaluated, namely the extension of the front and the dispersion along the front. The effectiveness and capacity of the proposed approach are shown through simulations tests.

Abstract

Abstract
Diffusion of innovation is a research topic which has been subject to several works in the last years. The diffusion of innovation theory aims to explain how new ideas and practices are disseminated between the members of a social system. A significant part of the existing models are based on the use of parameters which determine the process of innovation adoption, and rely on simple mathematical functions centered in the observation and description of diffusion patterns. This models enable a more explicit diffusion process study, but its use involves the estimation of diffusion coefficients, usually obtained from historical data or chronological series. This raises some problems, for instance when there is no data or it is insufficient. This paper proposes the use of evolutionary computation is an alternative approach for the simulation of innovation diffusion within organizations, in order to overcome some of the problems inherent to the existing models.

Abstract
This paper proposes a new algorithm which promotes well distributed non-dominated fronts in the parameters space when a single-objective function is optimized. This algorithm is based on e-dominance concept and maxmin sorting scheme. Besides that, the paper also presents the results of the algorithm when it is used in the automated synthesis of optimum performance CMOS radio-frequency and microwave binary-weighted differential switched capacitor arrays (RFDSCAs). The genetic synthesis tool optimizes a fitness function which is based on the performance parameter of the RFDSCAs. To validate the proposed design methodology, a CMOS RFDSCA is synthesized, using a 0.25 µm BiCMOS technology.