In this paper, we present optimal control for movement and trajectory planning for four degrees-of-freedom robot using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs) for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like; Movement, Friction and Settling Time in robotic arm movement have been compensated using Fuz...

In this paper, we present a simulated annealing (SA) and a genetic algorithm (GA) based on heuristics for scheduling problem of jobs in virtual cellular manufacturing systems. A virtual manufacturing cell (VMC) is a group of resources that is dedicated to the manufacturing of a part family. Although this grouping is not reflected in the physical structure of the manufacturing system, but machin...

This chapter introduces three new multi-objective genetic algorithms (MOGAs) for minimum distributions of both actuators and sensors within seismically excited large-scale civil structures such that the structural responses are also minimized. The first MOGA is developed through the integration of Implicit Redundant Representation (IRR), Genetic Algorithm (GA), and Non-dominated sorting GA 2 (N...

In this paper, we propose five data fusion schemes for the Internet of Things (IoT) scenario,which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re-GAPSO), Genetic Algorithm and Artificial Neural Network (GA-ANN), Rough and Perceptron (Ro-P)and Rough and GAPSO (Ro-GAPSO). All the schemes consist of four stages, including preprocessingthe data set ba...

Researchers have proposed several Genetic Algorithm (GA) based crisp clustering algorithms. Rough clustering based on Genetic Algorithms, Kohonen Self-Organizing Maps, K-means algorithm are also reported in literature. Recently, researchers have combined GAs with iterative rough clustering algorithms such as K-means and K-Medoids. Use of GAs makes it possible to specify explicit optimization of...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

in this paper, a new approach is proposed for the optimum design of single-phase induction motor. by using the classical design equations and the evolutionary algorithms such as genetic algorithms (ga), particle swarm optimization (pso) and modified particle swarm optimization (mpso), a single phase induction motor (spim) was designed with the maximum efficiency. the finite element method (fem)...

This paper presents implementations of genetic algorithms in a tree shape parallel computer architecture. Diierent levels of parallelism involved in GAs are studied. In addition, basic models for parallel GAs are considered. The tree shape parallel computer system, GAPA (Genetic Algorithm Parallel Accelerator), is described in detail, including architecture and special hardware for GA computati...

In this paper, a multi-product single machine scheduling problem with the possibility of producing defected jobs, is considered. We concern rework in the scheduling environment and propose a mixed-integer programming (MIP) model for the problem.  Based on the philosophy of just-in-time production, minimization of the sum of earliness and tardiness costs is taken into account as the objective fu...