Design optimization of structures with discrete and continuous search spaces is a complex optimization problem with lots of local optima. Metaheuristic optimization algorithms, due to not requiring gradient information of the objective function, are efficient tools for solving these problems at a reasonable computational time. In this paper, the Doppler Effect-Mean Euclidian Distance Threshold ...

Ant colony optimization algorithms (ACOs) have been basically introduced to discrete variable problems and applied to different research domains in several engineering fields. Meanwhile, abundant studies have been already involved to adapt different ant models to continuous search spaces. Assessments indicate competitive performance of ACOs on discrete or continuous domains. Therefore, as poten...

Most real world engineering design problems, such as cross-country water mains, include combinations of continuous, discrete, and binary value decision variables. Very often, the binary decision variables associate with the presence and/or absence of some nominated alternatives or project’s components. This study extends an existing continuous Ant Colony Optimization (ACO) algorithm to simultan...

In this paper, Lagrange interpolation in Chebyshev-Gauss-Lobatto nodes is used to develop a procedure for finding discrete and continuous approximate solutions of a singular boundary value problem. At first, a continuous time optimization problem related to the original singular boundary value problem is proposed. Then, using the Chebyshev- Gauss-Lobatto nodes, we convert the continuous time op...

Modern machine learning and data analysis hinge on sophisticated search techniques. In general, exploration in high-dimensional and multi-modal spaces is needed. Some algorithms that imitate certain natural principles, the so-called evolutionary algorithms, have been used in different aspects of Environmental Science and have found numerous applications in Environmental related problems. In thi...

Many methods have been developed for structural size and configuration optimization in which cross-sectional areas are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. This paper proposes two efficient structural optimization methods based on the harmony search (HS) heuristic algorithm that treat both discret...

Scalability of optimization algorithms is a major challenge in coping with the ever-growing size problems wide range application areas from high-dimensional machine learning to complex large-scale engineering problems. The field global concerned improving scalability algorithms, particularly, population-based metaheuristics. Such metaheuristics have been successfully applied continuous, discret...