Evolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), F...

The analysis of flow in water-distribution networks with several pumps by the Content Model may be turned into a non-convex optimization uncertain problem with multiple solutions. Newton-based methods such as GGA are not able to capture a global optimum in these situations. On the other hand, evolutionary methods designed to use the population of individuals may find a global solution even for ...

Optimization of turning process is a non-linear optimization with constrains and it is difficult for the conventional optimization algorithms to solve this problem. The purpose of present study is to demonstrate the potential of Imperialist Competitive Algorithm (ICA) for optimization of multipass turning process. This algorithm is inspired by competition mechanism among imperialists and coloni...

Optimum parameters of Tuned Mass Dampers (TMD) are determined in this paper to minimize dynamic response of a multi-storied building system. The response of the structural system is simulated under lateral excitation. To optimize dynamic parameters of the TMD system for minimum top deflection of the structure, a numerical global optimization algorithm called Evolutionary Operation (EVOP) is use...

Robust topology optimization has gained importance during the last years. This paper presents a robust approach to topology optimization using multiobjective evolutionary algorithms. A key contribution of our approach is that our optimization model handles structural robustness through the first two objectives, namely, the expected compliance and its variance; whereas a third objective incorpor...

This paper describes a penalty-free multi-objective evolutionary optimization approach for the phased whole-life design and rehabilitation of water distribution systems. The optimization model considers the initial construction, rehabilitation and upgrading costs. Repairs and pipe failure costs are included. The model also takes into consideration the deterioration over time of both the structu...

Aerodynamic design optimization of an airfoil for the Mars exploration airplane has been demonstrated by using an evolutionary algorithm. The adaptive range genetic algorithm is used for efficient and robust design optimization. Two-dimensional Navier-Stokes solver is used for accurate aerodynamic performance evaluation. The present computation is parallelized on the SX-6 vector computers in In...

A probabilistic evolutionary framework is presented and shown to be applicable to both learning and optimization problems. In this framework, evolutionary computation is viewed as Bayesian inference that iteratively updates the posterior distribution of a population from the prior knowledge and observation of new individuals to find an individual with the maximum posterior probability. Theoreti...

Multiple, often conflicting objectives arise naturally in most real-world optimization scenarios. As evolutionary algorithms possess several characteristics that are desirable for this type of problem, this class of search strategies has been used for multiobjective optimization for more than a decade. Meanwhile evolutionary multiobjective optimization has become established as a separate subdi...

In the structural optimization problem, the aim is to decrease the amount of structural costs and weight, but the safety of platform should not violate the individual limits enforced by offshore codes. The outer diameter and thickness of members are two important variables in the optimization process and their final dimensions should be obtained according to the optimization algorithms such as ...