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Sizing optimization of truss structures using flower pollination algorithm

Graphical abstractDisplay Omitted Truss sizing optimization with flower pollination algorithm.Good balance of global and local search.Iterative constraint handling strategy to accept or reject trial designs.Optimized designs are competitive with metaheuristic optimization literature. The recently developed flower pollination algorithm is used to minimize the weight of truss structures, including sizing design variables. The new algorithm can efficiently combine local and global searches, inspired by cross-pollination and self-pollination of flowering plants, respectively. Furthermore, it implements an iterative constraint handling strategy where trial designs are accepted or rejected based on the allowed amount of constraint violation that is progressively reduced as the search process approaches the optimum. This strategy aims to obtain always feasible optimized designs. The new algorithm is tested using three classical sizing optimization problems of 2D and 3D truss structures. Optimization results show that the proposed method is competitive with other state-of-the-art metaheuristic algorithms presented in the literature.

Application of the Flower Pollination Algorithm in Structural Engineering

In the design of a structural system, the optimum values of design variables cannot be derived analytically. Structural engineering problems have various design constraints concerning structural security measures and practicability in production. Thus, optimization becomes an important part of the design process. Recent studies suggested that metaheuristic methods using random search procedures are effective for solving optimization problems in structural engineering. In this chapter, the flower pollination algorithm (FPA) is presented for dealing with structural engineering problems. The engineering problems are about pin-jointed plane frames, truss systems, deflection minimization of I-beams, tubular columns, and cantilever beams. The FPA inspired from the reproduction of flowers via pollination is effective to find the best optimum results when compared to other methods. In addition, the computing time is usually shorter and the optimum results are also robust.

Optimization of seismic isolation systems via harmony search

In this article, the optimization of isolation system parameters via the harmony search (HS) optimization method is proposed for seismically isolated buildings subjected to both near-fault and far-fault earthquakes. To obtain optimum values of isolation system parameters, an optimization program was developed in Matlab/Simulink employing the HS algorithm. The objective was to obtain a set of isolation system parameters within a defined range that minimizes the acceleration response of a seismically isolated structure subjected to various earthquakes without exceeding a peak isolation system displacement limit. Several cases were investigated for different isolation system damping ratios and peak displacement limitations of seismic isolation devices. Time history analyses were repeated for the neighbouring parameters of optimum values and the results proved that the parameters determined via HS were true optima. The performance of the optimum isolation system was tested under a second set of earthquakes that was different from the first set used in the optimization process. The proposed optimization approach is applicable to linear isolation systems. Isolation systems composed of isolation elements that are inherently nonlinear are the subject of a future study. Investigation of the optimum isolation system parameters has been considered in parametric studies. However, obtaining the best performance of a seismic isolation system requires a true optimization by taking the possibility of both near-fault and far-fault earthquakes into account. HS optimization is proposed here as a viable solution to this problem.

Optimum Tuning of Mass Dampers by Using a Hybrid Method Using Harmony Search and Flower Pollination Algorithm

In this study, a new approach is proposed for optimization of tuned mass damper positioned on the top of seismic structures. The usage of metaheuristic algorithms is a well-known and effective technique for optimum tuning of parameters such as mass, period and damping ratio. The aim of the study is to generate a new methodology in order to improve the computation capacity and precision of the final results. For that reason, harmony search (HS) and flower pollination algorithm (FPA) are hybridized by proposing a probability based approach. In the methodology, global and local search processes of HS are used together with global and local pollination stages of FPA. In that case, four different types of generation are used. In the methodology, these four types of generation have the same chance at the start of the optimization process and probabilities are reduced when the corresponding type of the generation is chosen. If an improvement is provided for the objective of the optimization, the probability of the effective type is increased. The proposed method has an effective convergence by providing improvement of the optimization objective comparing to classical FPA.

Review and Applications of Metaheuristic Algorithms in Civil Engineering

Many design optimization problems in civil engineering are highly nonlinear and can be challenging to solve using traditional methods. In many cases, metaheurisitc algorithms can be an effective alternative and thus suitable in civil engineering applications. In this chapter, metaheuristic algorithms in civil engineering problems are briefly presented and recent applications are discussed. Two case studies such as the optimization of tuned mass dampers and cost optimization of reinforced concrete beams are analyzed.

Space applications of tensegric structures

Tensile integrity (tensegrity, tensegric) structures are suggested for possible use in outer space and on space bodies because of their minimal need for structural materials, ease of transfer and mounting. Structurally their behavior is non-linear. It has been shown here that their structural analysis can successfully be performed by total potential optimization using meta-heuristic algorithms (TPO/MA). The named method is an emerging technique that combines minimum energy principle of mechanics with metaheuristic algorithms. The technique thus defined has been shown to be very efficient, accurate and robust in analyzing structures. The success of the technique is especially profound for non-linear structures. In this study the named technique is applied to tensile integrity (tensegrity, tensegric) structures which are known to be highly nonlinear, thus difficult to analyze.

Optimization of Tuned Mass Damper with Harmony Search

Harmony search (HS), a metaheuristic optimization method that has been successfully proven by optimizing several engineering problems, is a suitable algorithm for tuning passive mass dampers on structures. By adapting HS to a tuned mass damper (TMD) problem, the optimum mass, stiffness, and damping coefficients of TMDs are proposed under external excitations. The physical and economical restriction can be also taken into account by limiting the soloution ranges. Considering physical and economic conditions is not possible by using the closed form expressions depending on a preselected damper mass. A program can be developed for numerical optimization and time domain simulation by using different optimization strategies. The method was presented by analyzing two examples. In the first example, the optimization process was conducted under a sinus loading for a fast and general optimization. The other example was analyzed under earthquake excitations for specific conditions. The optimum TMD parameters were checked under benchmark earthquakes, which were not considered during optimization. Also, the optimum results of the first example were compared with several other documented methods. Comparisons show that the HS approach is more effective than other documented methods in reducing structural vibrations and more feasible due to suitable TMD parameters according to physical and economic conditions.

A Comprehensive Review of the Flower Pollination Algorithm for Solving Engineering Problems

Engineering optimization problems are often solved by using metaheuristic algorithms. Flower pollination algorithm (FPA) is a nature-inspired metaheuristic algorithm and FPA have been used in a variety of engineering problems. In this book chapter, the engineering applications of FPA and its variants are reviewed, and the applications include chemical engineering, civil engineering, energy and power systems, mechanical engineering, electronical and communication engineering, computer science and others. Further research topics are also outlined.

Metaheuristic Based Optimization for Tuned Mass Dampers Using Frequency Domain Responses

The usage of tuned mass dampers is a practical technique for civil structures under undesired vibrations. Since earthquake or other excitations have random vibration with various frequencies, frequency domain responses of structures can be used in tuning of mass dampers. By the minimization of transfer function of the structure, the amplitude corresponding to the response frequency of the structure is minimized. Thus, the passive control of the structure is provided. The optimization problem is non-linear since the existence of inherent damping of the structure, possible solution range of tuned mass damper (TMD) and multiple modes of multiple degree of freedom structures. For that reason, three metaheuristic algorithms such as harmony search, flower pollination algorithm and teaching learning based optimization are compared in mean of performance and computation effort. All algorithms are feasible with significant possible advantages.

Optimum Reinforced Concrete Design by Harmony Search Algorithm

The music-inspired metaheuristic method, called harmony search (HS), is an effective tool in optimization of engineering design problems. HS has been applied for the optimum design of reinforced concrete (RC) members so as to find the best solution, balancing the usability of the design and economy. In this chapter, the optimum design of RC members is presented after optimization of RC members. Then, HS-based optimization applications, such as RC slender columns, RC shear walls, and post-tensioned RC axially symmetric cylindrical walls, are also discussed. The HS-based methods are feasible in finding the optimum design in such problems.