During the past decade, solving complex optimization problems with metaheuristic algorithms has received considerable attention among practitioners and researchers. Hence, many metaheuristic algorithms have been developed over the last years. Many of these algorithms are inspired by various phenomena of nature. In this paper, a new population based algorithm, the Lion Optimization Algorithm (LO...

Particle swarm optimization is a metaheuristic technique widely applied to solve various optimization problems as well as parameter selection problems for various classification techniques. This paper presents an approach for linear support vector machines classifier optimization combining its selection from a family of similar classifiers with parameter optimization. Experimental results indic...

Nature computing has evolved with exciting performance to solve complex real-world combinatorial optimization problems. These problems span across engineering, medical sciences, and sciences generally. The Ebola virus a propagation strategy that allows individuals in population move among susceptible, infected, quarantined, hospitalized, recovered, dead sub-population groups. Motivated by the e...

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 ...

The main focus of this paper is to optimize the coverage each 4G LTE network cell within service area. There are many algorithms can be implemented determine optimal area including deterministic and heuristic approaches. approach could solve accurately optimization problem but need more resources time consuming convergence parameters. Therefore, approaches were introduced improve drawback. meth...

In this paper, a new robust metaheuristic optimization algorithm called improved time evolutionary optimization (ITEO) is applied to design reinforced concrete one-way ribbed slabs. Geometric and strength characteristics of concrete slabs are considered as design variables. The optimal design is such that in addition to achieving the minimum cost, all design constraints are satisfied under Amer...

The main purpose of the present work is to investigate the impact of soil-structure interaction on performance-based design optimization of steel moment resisting frame (MRF) structures. To this end, the seismic performance of optimally designed MRFs with rigid supports is compared with that of the optimal designs with a flexible base in the context of performance-based design. Two efficient me...