optimization techniques can be efficiently utilized to achieve an optimal shape for arch dams. this optimal design can consider the conditions of the economy and safety simultaneously. the main aim is to present an applicable and practical model and suggest an algorithm for optimization of concrete arch dams to enhance their seismic performance. to achieve this purpose, a preliminary optimizati...

the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

In this age of wireless communication, micro strip antennas have drawn maximum attention of antenna community because of its compact size, light weight and low profile configuration. In this paper the problem of locating feed point of an inset fed microstrip patch antenna designed for wireless communication is dealt with. The optimization is done using three techniques: Genetic Optimization (GA...

This paper introduces an effectual technique to solve the DNA sequence assembly problem using a variance of the standard Particle Swarm Optimization (PSO) called the Constriction factor Particle Swarm Optimization (CPSO).The problem of sequence assembly is one of the primary problems in computational molecular biology that requires optimization methodologies to rebuild the original DNA sequence...

In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...

in this paper particle swarm optimization with smart inertia factor (pso-sif) algorithm is proposed to solve combined heat and power economic dispatch (chped) problem. the chped problem is one of the most important problems in power systems and is a challenging non-convex and non-linear optimization problem. the aim of solving chped problem is to determine optimal heat and power of generating u...

this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...