O. Hasançebi

Optimal design of planar and space structures with genetic algorithms

Abstract One of the most important practical considerations in the optimization of steel structures is that structural members are generally to be selected from available steel profiles. Furthermore, the solutions produced according to the national specifications are undoubtedly valuable from the point of view of applicability in real-life practice. This paper reports the development of a computer-based systematic approach for discrete optimal design of planar and space structures composed of one-dimensional elements. The main characteristic of the solution methodology is the use of a genetic algorithm (GA) as the optimizer. Applications and experience on steel frame and truss structures are discussed. The results of comparative studies of the GA against other various discrete and continuous optimization algorithms for a class of representative structural design problems are reported to show the efficiency of the former. It is observed that a GA often finds the region of the search space containing the global optimum, but not the true optimum itself. Also, in this study an approach based on a proposed multilevel optimization is tested and proved to overcome this shortcoming.

Adaptive Harmony Search Method for Structural Optimization

This paper presents an adaptive harmony search algorithm for solving structural optimization problems. The harmony memory considering rate and pitch adjusting rate are conceived as the two main parameters of the technique for generating new solution vectors. In the standard implementation of the technique appropriate constant values are assigned to these parameters following a sensitivity analysis for each problem considered. The success of the optimization process is directly related on a chosen parameter value set. The adaptive harmony search algorithm proposed here incorporates a new approach for adjusting these parameters automatically during the search for the most efficient optimization process. The efficiency of the proposed algorithm is numerically investigated using two large-scale steel frameworks that are designed for minimum weight according to the provisions of ASD-AISC specification. The solutions obtained are compared with those of the standard algorithm as well as of the other metaheuristic search techniques. It is shown that the proposed algorithm improves performance of the technique and it renders unnecessary the initial selection of the harmony search parameters.

Layout optimisation of trusses using simulated annealing

This paper addresses to the development of a simulated annealing (SA) based solution algorithm for the simultaneous optimum design of truss type structures with respect to size, shape and topology design variables. The proposed algorithm is designed in such way that together with applicability to practical design problems, it also aims to produce efficient and improved design solutions for the problems of interest. From the practical point of view, the objective chosen is to minimise the weight of the structures under a set of particular constraints imposed by design code specifications on nodal displacement, member stress and stability. Concerning the efficiency of the algorithm, SA is adapted to be able to work fruitfully in the design spaces of complex problems occupied by many regions of highly different characteristics. The proposed algorithm is tested on two large design example problems taken from the literature for comparison purposes and the results are fully discussed.

Evaluation of crossover techniques in genetic algorithm based optimum structural design

Abstract Crossover is one of the three basic operators in any genetic algorithm (GA). Several crossover techniques have been proposed and their relative merits are currently under investigation. This paper starts with a brief discussion of the working scheme of the GAs and the crossover techniques commonly used in previous GA applications. Next, these techniques are tested on two truss size optimization problems, and are evaluated with respect to exploration and exploitation aspects of the search process. Finally, the paper proposes two newly developed crossover techniques, through which a better efficiency of GAs can be obtained. Comparative studies are carried out between the proposed and the common crossover techniques, and the results are fully discussed.

Metaheuristics in structural optimization and discussions on harmony search algorithm

Abstract Metaheuristic algorithms have provided efficient tools to engineering designers by which it became possible to determine the optimum solutions of engineering design optimization problems encountered in every day practice. Generally metaheuristics are based on metaphors that are taken from nature or some other processes. Because of their success of providing solutions to complex engineering design optimization problems the recent literature has flourished with a large number of new metaheuristics based on a variety of metaphors. Despite the fact that most of these techniques have numerically proven themselves as reliable and strong tools for solutions of design optimization problems in many different disciplines, some argue against these methods on account of not having mathematical background and making use of irrelevant and odd metaphors. However, so long as these efforts bring about computationally efficient and robust optimum structural tools for designers what type of metaphors they are based on becomes insignificant. After a brief historical review of structural optimization this article opens this issue up for discussion of the readers and attempts to answer some of the criticisms asserted in some recent publications related with the novelty of metaheuristics.

Discrete size optimization of steel trusses using a refined big bang–big crunch algorithm

This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang–big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.

Bat inspired algorithm for discrete size optimization of steel frames

Bat inspired (BI) algorithm is a recently developed metaheuristic optimization technique inspired by echolocation behavior of bats. In this study, the BI algorithm is examined in the context of discrete size optimization of steel frames designed for minimum weight. In the optimum design problem frame members are selected from available set of steel sections for producing practically acceptable designs subject to strength and displacement provisions of American Institute of Steel Construction-Allowable Stress Design (AISC-ASD) specification. The performance of the technique is quantified using three real-size large steel frames under actual load and design considerations. The results obtained provide a sufficient evidence for successful performance of the BI algorithm in comparison to other metaheuristics employed in structural optimization.

Upper bound strategy for metaheuristic based design optimization of steel frames

Optimum design of structural systems based on metaheuristic algorithms suffers from enormously time-consuming structural analyses to locate a reasonable design. In this paper an upper bound strategy (UBS) is proposed for reducing the total number of structural analyses in metaheuristic based design optimization of steel frame structures. The well-known big bang-big crunch algorithm as well as its two enhanced variants are adopted as typical metaheuristic algorithms to evaluate the effect of the UBS on computational efficiency of these techniques. The numerical results reveal that the UBS can significantly lessen the total computational cost in metaheuristic based design optimization of steel frames.

An elitist self-adaptive step-size search for structural design optimization

Abstract This paper presents a method for optimal sizing of truss structures based on a refined self-adaptive step-size search (SASS) algorithm. An elitist self-adaptive step-size search (ESASS) algorithm is proposed wherein two approaches are considered for improving (i) convergence accuracy, and (ii) computational efficiency. In the first approach an additional randomness is incorporated into the sampling step of the technique to preserve exploration capability of the algorithm during the optimization. Furthermore, an adaptive sampling scheme is introduced to enhance quality of the final solutions. In the second approach computational efficiency of the technique is accelerated through avoiding unnecessary analyses throughout the optimization process using the so-called upper bound strategy (UBS). The numerical results indicate the efficiency of the proposed ESASS algorithm.

Harmony Search Algorithms in Structural Engineering

Harmony search method is widely applied in structural design optimization since its emergence. These applications have shown that harmony search algorithm is robust, effective and reliable optimization method. Within recent years several enhancements are suggested to improve the performance of the algorithm. Among these Mahdavi has presented two versions of harmony search methods. He named these as improved harmony search method and global best harmony search method. Saka and Hasancebi (2009) have suggested adaptive harmony search where the harmony search parameters are adjusted automatically during design iterations. Coelho has proposed improved harmony search method. He suggested an expression for one of the parameters of standard harmony search method. In this chapter, the optimum design problem of steel space frames is formulated according to the provisions of LRFD-AISC (Load and Resistance Factor Design-American Institute of Steel Corporation). The weight of the steel frame is taken as the objective function to be minimized. Seven different structural optimization algorithms are developed each of which are based on one of the above mentioned versions of harmony search method. Three real size steel frames are designed using each of these algorithms. The optimum designs obtained by these techniques are compared and performance of each version is evaluated.