a new meta-heuristic method, based on neuronal communication (nc), is introduced in this article. the neuronal communication illustrates how data is exchanged between neurons in neural system. actually, this pattern works efficiently in the nature. the present paper shows it is the same to find the global minimum. in addition, since few numbers of neurons participate in each step of the method,...

Many real-world search and optimization problems involve inequality and/or equality constraints and are thus posed as constrained optimization problems. In trying to solve constrained optimization problems using classical optimization methods, this paper presents a Multi-Objective Bees Algorithm (MOBA) for solving the multi-objective optimal of mechanical engineering problems design. In the pre...

This paper presents an effective optimization method for nonlinear constrained optimization of retaining structures. A newly developed heuristic global optimization algorithm called gravitational search algorithm (GSA) is introduced and applied for the optimization of retaining structures. The optimization procedure controls all geotechnical and structural design constraints while reducing the ...

In this article, an Advanced Charged System Search (ACSS) algorithm is applied for the optimum design of steel structures. ACSS uses the idea of Opposition-based Learning and Levy flight to enhance the optimization abilities of the standard CSS. It also utilizes the information of the position of each charged particle in the subsequent search process to increase the convergence speed. The objec...

In rigid plastic analysis one of the most widely applicable methods that is based on the minimum principle, is the combination of elementary mechanisms which uses the upper bound theorem. In this method a mechanism is searched which corresponds to the smallest load factor. Mathematical programming can be used to optimize this search process for simple fra...

Evolution Strategies (ES) are a class of Evolutionary Algorithms based on Gaussian mutation and deterministic selection. Gaussian mutation captures pair-wise dependencies between the variables through a covariance matrix. Covariance Matrix Adaptation (CMA) is a method to update this covariance matrix. In this paper, the CMA-ES, which has found many applications in solving continuous optimizatio...

In this paper we propose an approach to solve multi-objective structural design problem using basic t-norm based fuzzy optimization programming technique. Here a planer truss structural model in fuzzy environment has been developed. In this structural model formulation, the objective functions are the weight of the truss and the vertical deflection of loaded joint; the design variables are the ...

In this paper the recently developed meta-heuristic optimization method, known as charged system search (CSS), is utilized for optimum nodal ordering to minimize bandwidth and profile of sparse matrices. The CSS is an optimization algorithm, which is based on the governing laws of Coulomb and Gauss from electrostatics and the Newtonian mechanics of motion. The bandwidth and profile of some grap...

in this paper, the problem of simultaneous shape and size optimization of single-layer barrel vault frames which contains both of discrete and continuous variables is addressed. in this method, the improved magnetic charged system search (imcss) is utilized as the optimization algorithm and the open application programming interface (oapi) plays the role of interfacing analysis software with th...