The design of many engineering systems can be a complex process, which means many possibilities and factors must be considered during problem formulation. The process of searching for a design that meets both performance and safety standards with reliable impact is the goal of structural optimization. Structural optimization is an approach whereby the structural design is subjected to being optimized in terms of weight while maintaining all design constraints such as stress, strain, and stability. Structural design optimization problems involve searching for the minimum of the stated objective function, usually the weight of the structure and constructability. Trusses are triangular frame works in which the members are subjected to essentially axial forces due to externally applied load at the joints only. Truss structures can be optimized by varying the structure's size, shape, and topology. Although combining these three prototypes of optimization can ultimately a yield better result, the underlying mathematical model becomes complicated. Over the last decade, new optimization strategies based on metaheuristic algorithms have been devised to obtain the optimal design for structural systems. Harmony search (HS) is a metaheuristic algorithm proposed by Geem et al., inspired by the observation that the aim of music is to search for a perfect state of harmony. In this research, the implementation of HS algorithm has been applied to optimize the size of truss structures that results in the weight reduction of the truss members. The results obtained with HS were compared to those obtained from the original sizes before optimization, to verify the influence on the optimal design of truss structures subjected to stresses, deflections, vertical and lateral displacements, and buckling constrains.

Various structures, such as buildings, bridges, and paved roads play an important role in our lives. However, these construction projects require large expenditures. Designing infrastructure cost-efficiently while satisfying all necessary design constraints is one of the most important and difficult tasks for a structural engineer. Traditionally, mathematical gradient-based optimization techniques have been applied to these designs. However, these gradient-based methods are not suitable for discrete design variables such as factory-made cross sectional area of structural members. Recently, researchers have turned their interest to phenomenon-mimicking optimization techniques because these techniques have proved able to efficiently handle discrete design variables. One of these techniques is harmony search, an algorithm developed from musical improvisation that has been applied to various structural design problems and has demonstrated cost-savings. This book gathers all the latest developments relating to the application of the harmony search algorithm in the structural design field in order for readers to efficiently understand the full spectrum of the algorithm’s potential and to easily apply the algorithm to their own structural problems. This book contains six chapters with the following subjects: standard harmony search algorithm and its applications by Lee; standard harmony search algorithm for steel frame design by Degertekin; adaptive harmony search algorithm and its applications by Saka and Hasançebi; harmony particle swarm algorithm and its applications by Li and Liu; hybrid algorithm of harmony search, particle swarm & ant colony for structural design by Kaveh and Talatahari; and parameter calibration of viscoelastic and damage functions by Mun and Geem.

When a truss structure is to be designed two important questions should be answered. First, how should the truss that requires the minimum amount of materials look like? Second, what are the possible members' cross sectional areas that support the applied load safely? In this work those two questions are answered using a two stage optimization process. In stage one, starting with hyper-connected truss ground structures that fully encompass the design region, together with specified support conditions and load cases, the discrete combinations and arrangement of truss members that will yield the lightest and stiffest structure are sought. In the second stage the minimum cross sectional areas of the members that satisfy the imposed constraints are sought. In both stages harmony search algorithms are employed. These represent one of the most recent heuristic, stochastic search optimization methods that, while relatively simple and robust, overcome some of the drawbacks of preceding search techniques such as: the ability to converge to a global optimum, and the ability to optimize non-differentiable and non-continuous functions. The viability of the proposed framework is documented on numerous benchmark problems from the literature.

Civil engineering structures such as buildings, bridges, stadiums, and offshore structures play an import role in our daily life. However, constructing these structures requires lots of budget. Thus, how to cost-efficiently design structures satisfying all required design constraints is an important factor to structural engineers. Traditionally, mathematical gradient-based optimal techniques have been applied to the design of optimal structures. While, many practical engineering optimal problems are very complex and hard to solve by traditional method. In the past few decades, swarm intelligence algorithms, which were inspired by the social behaviour of natural animals such as fish schooling and bird flocking, were developed because they do not require conventional mathematical assumptions and thus possess better global search abilities than the traditional optimization algorithms and have attracted more and more attention. These intelligent based algorithms are very suitable for continuous and discrete design variable problems such as ready-made structural members and have been vigorously applied to various structural design problems and obtained good results. This book gathers the authors’ latest research work related with particle swarm optimizer algorithm and group search optimizer algorithm as well as their application to structural optimal design. The readers can understand the full spectrum of the algorithms and apply the algorithms to their own research problems.

Various structures, such as buildings, bridges, and paved roads play an important role in our lives. However, these construction projects require large expenditures. Designing infrastructure cost-efficiently while satisfying all necessary design constraints is one of the most important and difficult tasks for a structural engineer. Traditionally, mathematical gradient-based optimization techniques have been applied to these designs. However, these gradient-based methods are not suitable for discrete design variables such as factory-made cross sectional area of structural members. Recently, researchers have turned their interest to phenomenon-mimicking optimization techniques because these techniques have proved able to efficiently handle discrete design variables. One of these techniques is harmony search, an algorithm developed from musical improvisation that has been applied to various structural design problems and has demonstrated cost-savings. This book gathers all the latest developments relating to the application of the harmony search algorithm in the structural design field in order for readers to efficiently understand the full spectrum of the algorithm’s potential and to easily apply the algorithm to their own structural problems. This book contains six chapters with the following subjects: standard harmony search algorithm and its applications by Lee; standard harmony search algorithm for steel frame design by Degertekin; adaptive harmony search algorithm and its applications by Saka and Hasançebi; harmony particle swarm algorithm and its applications by Li and Liu; hybrid algorithm of harmony search, particle swarm & ant colony for structural design by Kaveh and Talatahari; and parameter calibration of viscoelastic and damage functions by Mun and Geem.

This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally be utilized for optimal design of other systems such as hydraulic and electrical networks. In the second edition seven new chapters are added consisting of the new developments in the field of optimization. These chapters consist of the Enhanced Colliding Bodies Optimization, Global Sensitivity Analysis, Tug of War Optimization, Water Evaporation Optimization, Vibrating Particle System Optimization and Cyclical Parthenogenesis Optimization algorithms. A chapter is also devoted to optimal design of large scale structures.