The aim of this paper is to obtain the optimal design of trusses under uncertain static loads. Genetic algorithms are used to carry out the structural optimization and convex models are employed to handle the uncertainties. A study of the efficiency of genetic algorithms is performed. Using the uniform bound convex model affects the computational speed of the algorithm. In fact, it requires as ...

Rolling-element bearings are widely used in various mechanical and electrical systems. A reliable online bearing fault diagnostic technique is critically needed in industries to detect the occurrence of a fault so as to prevent system’s performance degradation and malfunction. To improve the fault diagnostic reliability and efficiency, a genetic algorithm based feature optimization technique is...

The efficiency of transportation system management plays an important role in the planning and operation efficiency of flexible manufacturing systems. Automated Guided Vehicles (AGV) are part of diversified and advanced techniques in the field of material transportation which have many applications today and act as an intermediary between operating and storage equipment and are routed and contr...

This paper presents an effective optimization method for nonlinear constrained optimization of retaining structures. A newly developed heuristic global optimization algorithm called gravitational search algorithm (GSA) is introduced and applied for the optimization of retaining structures. The optimization procedure controls all geotechnical and structural design constraints while reducing the ...

Two methods for ranking of solutions of multi objective optimization problems are proposed in this paper. The methods can be used, e.g. by metaheuristics to select good solutions from a set of non dominated solutions. They are suitable for population based metaheuristics to limit the size of the population. It is shown theoretically that the ranking methods possess some interesting properties f...

this paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. in this research, cells are defined as a queue system which will be optimized via queuing theory. in this queue system, each machine is assumed as a server and each part as a customer. the grouping of machines and parts...

Practical optimization methods including genetic algorithms are introduced, based on evolutionary computing or soft computing. Several application examples are presented to demonstrate and discuss the efficiency and applicability of the described methods.

In this paper, a new automatic scheme to register retinal images is presented and is currently tested in a clinical environment. The scheme considers the suitability and efficiency of different image transformation models and function optimization techniques, following an initial preprocessing stage. Three different transformation models -Affine, Bilinear and Projectiveas well as two global opt...