A new method of optimization on linear parabolic solar collectors using exergy analysis is presented. A comprehensive mathematical modeling of thermal and optical performance is simulated and geometrical and thermodynamic parameters were assumed as optimization variables. By applying a derived expression for exergy efficiency, exergy losses were generated and the optimum design and operating co...

this study is investigated the optimum parameters for a tuned mass damper (tmd) under the seismic excitation. shuffled complex evolution (sce) is a meta-heuristic optimization method which is used to find the optimum damping and tuning frequency ratio for a tmd. the efficiency of the tmd is evaluated by decreasing the structural displacement dynamic magnification factor (ddmf) and acceleration ...

The reduction of cost in the process of iron manufacture is of permanent interest in steel-making industry. An important part of the overall cost in the process of iron manufacture is the cost of production of metallurgical coke. This problem is solved by finding a new technologies of iron production (COREX) or optimization of current ways of iron production. Therefore we have adopted the metho...

This paper proposes a refined version of particle swarm optimization technique for the optimum design of steel structures. Swarm is composed of a number of particles and each particle in the swarm represents a candidate solution of the optimum design problem. Design constraints in accordance with ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution) are imposed by t...

Oil production optimization is one of the main targets of reservoir management. Smart well technology gives the ability of real time oil production optimization. Although this technology has many advantages; optimum adjustment or sizing of corresponding valves is still an issue to be solved. In this research, optimum port sizing of inflow control devices (ICDs) which are passive control valves ...

This paper proposes a novel optimization algorithm inspired by water flowing and shaking behaviors in a vessel. Water drops in our algorithm flow to the gradient descent direction and are sometimes shaken for getting out of local optimum areas when most water drops fall in local optimum areas. These flowing and shaking operations allow our algorithm to quickly approach to the global optimum wit...

Computational cost of metaheuristic based optimum design algorithms grows excessively with structure size. This results in computational inefficiency of modern metaheuristic algorithms in tackling optimum design problems of large scale structural systems. This paper attempts to provide a computationally efficient optimization tool for optimum design of large scale steel frame structures to AISC...

Most engineering optimization uses multiple objective functions rather than single objective function. To realize an artificial life algorithm based multi-objective optimization, this paper proposes a Pareto artificial life algorithm that is capable of searching Pareto set for multi-objective function solutions. The Pareto set of optimum solutions is found by applying two objective functions fo...

An effective and rigorous approach to determine optimum welding process parameters is implementation of advanced computer aided engineering (CAE) tool that integrates efficient optimization techniques and numerical welding simulation. In this paper, an automated computational methodology to determine optimum arc welding process control parameters is proposed. It is a coupled Genetic Algorithms ...

The evolutionary learning of fuzzy neural networks (FNN) consists of structure learning to determine the proper number of fuzzy rules and parameters learning to adjust the network parameters. Many optimization algorithms can be applied to evolve FNN. However the search space of most algorithms has fixed dimension, which cannot suit to dynamic structure learning of FNN. We propose a novel techni...