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A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. Cultural Algorithm (CA) utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.

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The current study presents an enhanced biogeography-based optimization (EBBO) algorithm for size and shape optimization of truss structures with natural frequency constraints. The BBO algorithm is one of the recently developed meta-heuristic algorithms inspired by the mathematical models in biogeography science and is based on the migration behavior of species among the habitats in the nature. In this study, the overall performance of the standard BBO algorithm is enhanced by new migration and mutation operators. The efficiency of the proposed algorithm is demonstrated by utilizing four benchmark truss design examples with frequency constraints. Numerical results show that the proposed EBBO algorithm not only significantly improves the performance of the standard BBO algorithm, but also finds competitive results compared with recently developed optimization methods.

Abstract-Developing autonomy among students has been one of the major concerns in second language instruction. Nowadays portfolio assessment as an alternative form to traditional evaluation has found its place in writing pedagogy. Present investigation was designed to study a group of thirty eight Iranian EFL learners with the aim of investigating the possible effects of using writing portfolio assessment on developing the ability of editing among Iranian EFL learners. The learners were asked to perform some writing tasks. Then they edited their own papers and corrected their writing products using the five categories of content, organization, grammar, spelling, and mechanics. There was a continuous dialogue between the teacher and the learners. The result indicated that the learners could be trai ned to use editing in their writing. Editing seems to be an effective way for higher proficiency learners to improve the organization of their writing.

This paper presents an optics inspired optimization (OIO) method for optimum design of steel tower structures with discrete variables. Inspired by the optical characteristics of concave and convex mirrors, OIO tries to solve optimization problem. In OIO, the surface of the objective function to be minimized is considered as a reflecting wavy mirror consisting of peaks and valleys.To generate a new solution (artificial image point) from a given solution (artificial object/light point) in the search space, it is assumed that the artificial ray glittered from the artificial light point is reflected back artificially by the function surface in which each peak is considered as a convex mirror and each valleys is treated as a concave mirror. Then, the artificial image point is formed by the theory of optics in Physics, and a new solution is generated in the search space accordingly. Numerical experiments have been conducted on 4 benchmark design examples with discrete variables, and the results obtained by OIO are compared to those reported in the literature. The results show that OIO can produce high quality solutions and show a relatively fast convergence rate. KEYWORDS discrete variables, optics inspired optimization, optimum design, tower structures 1 | INTRODUCTION Tower structures are, typically, considered high-rise and large scale structures composed of several hundred elements. They are among the tallest man-made structures. 1 This type of the structures has important applications in the electrical, telecommunication, and broadcasting industries.However, the design optimization of tower structures is a complex and real challenge. Evidence of this complexity is clear from simply glancing through many recently constructed tower structures, in which the existence of high number of design variables as well as the geometrical complexity make finding optimum design a challenging problem.In recent decades, the need for powerful and effective optimization techniques dealing with the structural optimum design problems has become widespread in the field of the structural engineering. [1][2][3][4][5][6][7][8][9][10] The objective of optimum discrete design problem of tower structures is to minimize the constructional costs of the structure under a number of design constraints. The constructional costs are commonly represented by the weight of the tower structure and the design constraints are the axial stresses and the nodal displacements, as well as assuring that the cross-sectional areas are economically available.There has been an increasing interest toward adaptive meta-heuristic optimization techniques inspired from physics, nature, and other disciplines for solving the structural discrete design problem optimally, [11,12] for the reason that they have relatively a powerful global searching capacity and simple framework. Examples are genetic algorithms (GAs), [4,13,14] particle swarm optimization (PSO), [15] ant colony optimization (ACO), [16] harmony search (HS) [17] algorithm, biogeography-based optimization (BBO)...