A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning ...

Harmony Search metaheuristic is successfully used in several applications of science and engineering. However, its effectiveness in solving multiobjective optimization problems using the concepts of Pareto optimality, remains unproved. This paper presents two proposals of the Harmony Search metaheuristic for multiobjective optimization, using the ZDT functions as a test bed. Performance metrics...

Wind farm layout optimization is to find the optimal positions of wind turbines inside a wind farm, so as to maximize and/or minimize a single objective or multiple objectives, while satisfying certain constraints. Most of the works in the literature divide the wind farm into cells in which turbines can be placed, hence, simplifying the problem from with continuous variables to with discrete va...

Harmony search algorithm is a meta-heuristic optimization method imitating the music improvisation process, where musicians improvise their instruments’ pitches searching for a perfect state of harmony. First, an improved harmony search algorithm is presented using the concept of swarm intelligence. Next, it is employed for training feedforward neural networks for three benchmark classification...

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimiza...

So far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is Particle Swarm Optimization (PSO). Prior some efforts by applying fuzzy logic for improving defects of PSO such as trapping in local optimums and early convergence has been done. Moreover to overcome the problem of i...

aim of this paper is to search and find ways and methods of constructivism teaching and learning ideas inteaching the architectural design studio. the objective is to extract all the positive things constructivism has to offer the architectural design studio for efficient teaching and effective learning. although there are similarities in the curricula of training architects all over the world,...

Optimization is one of the most important issues in all fields of science and engineering. There are two main categories for optimization problems: continues optimization and discrete optimization. Traditional methods, such as gradient descent, are used for solving continues optimization problems, But for discrete optimization, traditional and many new algorithms are introduced. Due to long tim...

This study presents a cost minimization model for the design of water distribution networks. The model uses a recently developed harmony search optimization algorithm while satisfying all the design constraints. The harmony search algorithm mimics a jazz improvisation process in order to find better design solutions, in this case pipe diameters in a water distribution network. The model also in...