عنوان مقاله [English]
Construction cost reduction for design engineers has always been important. However, reducing the cost of building should not reduce the quality of the structures. In other words, by providing an optimized design, the maximum capacity of the materials is used. In this study, to achieve these objectives, meta-heuristic algorithms perform the optimization. To optimize RC shear walls, meta-heuristic hybrid algorithm called firefly and particle swarm optimization (FA-PSO) is used. The results of this study confirm the efficiency and accuracy of the algorithm to achieve the global optimum. In this study, the optimal design of reinforced concrete shear walls is done by boundary element and seismic conditions. Cost of reinforced concrete shear wall includes the cost of materials (steel and concrete) and cost formwork, introduced as a goal function. Shear wall design criteria and constraints according to ACI Regulations are written. So the optimal point at the lowest cost is achieved when all constraints are met. In addition, the objective function is written in a manner that requires no database optimization done continuously. This collection is presented in the form of a program. This program is a graphical interface, allowing the user to enter information related to the shear walls
and outputs designed to easily observe. Two methods are provided to optimize the shear walls in this research. The first method is continuous optimization, and the second method is the continuous optimization while taking into account the dimensions of discrete variables to include construction conditions. One of the main advantages of this method compared to discrete is that there is no
need to create the database (Section database). This causes the application to review all design modes. The results show that plan is the most economical as possible due to the continuous optimization, as opposed to discrete method, which depends on a variety of databases and problem types.