Multiple Optimum Size/Shape/Topology Designs for Skeletal Structures Using a Genetic Algorithm

Balling, Richard; Briggs, Ryan R.; Gillman, Kevin

doi:10.1061/(asce)0733-9445(2006)132:7(1158)

Cited by 66 publications

(43 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The proposed algorithm supports topologic optimization by using methods proposed by Balling et al (2006) for optimization with a genetic algorithm. In particular, the specification of a member includes an option to mark it as removable.…”

Section: Accounting For Topologymentioning

confidence: 99%

“…In addition, when the maximum strength constraint value for a member is less than a specified threshold (the examples in this paper use 1:0 × 10 À4 ), that member is marked as spurious and the algorithm removes it. Balling et al (2006) provides further detail.…”

Section: Accounting For Topologymentioning

confidence: 99%

“…Hasancebi et al (2009) gives a thorough overview and comparison of such methods. Some researchers have noted that population-based methods have the potential to generate a range of viable alternatives, which can be more useful than developing a single best solution (Balling 2006;von Buelow 2007;Winslow 2008). One advantage is that fitness functions typically cannot account for considerations that are difficult to quantify, such as aesthetics and constructability.…”

Section: Introductionmentioning

confidence: 99%

“…Optimization methods that identify multiple locally optimal solutions are called multimodal. Balling et al (2006) and von Buelow (2007) have developed multimodal genetic algorithms for structural optimization, which have proven effective but computationally intensive. Examples in the Balling et al study used a population of 1,000 designs computed over 500 generations, meaning 500,000 model evaluations.…”

Section: Introductionmentioning

confidence: 99%

“…Examples in the Balling et al study used a population of 1,000 designs computed over 500 generations, meaning 500,000 model evaluations. Examples in the von Buelow (2007) study used a multilevel arrangement with a population of 20 topologies, each with 50 corresponding geometries, resulting in a total population of 1,000 that is run for hundreds of cycles, implying hundreds of thousands of model evaluations, similar to Balling et al (2006).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Harmony Search Method for Multimodal Size, Shape, and Topology Optimization of Structural Frameworks

Martini

2011

J. Struct. Eng.

View full text Add to dashboard Cite

This paper describes and demonstrates modifications of the harmony search method to support multimodal structural optimization. Several researchers have recognized the potential of population-based optimization methods, such as genetic algorithms and particle swarm optimization, to support multimodal optimization, that is, generating a range of good alternative solutions, rather than a single best solution. Among these population-based methods is the harmony search method, which has been demonstrated to be efficient and effective in many unimodal structural optimization problems. Toward the goal of making the harmony search method more effective in multimodal optimization, this paper describes a new strategy for generating solutions called close-harmony improvisation, and a new strategy for replacing solutions called local replacement. Examples demonstrate the effect of the two strategies used individually and in tandem. The discussion compares results with conventional harmony search and finds that close-harmony improvisation consistently improves the fitness of the search results, although the effect is sometimes mild, whereas local replacement is quite effective in increasing the diversity of the search result.

show abstract

Section: Accounting For Topologymentioning

confidence: 99%

Section: Accounting For Topologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Harmony Search Method for Multimodal Size, Shape, and Topology Optimization of Structural Frameworks

Martini

2011

J. Struct. Eng.

View full text Add to dashboard Cite

show abstract

Optimal control of nonlinear frames by Newmark and distributed genetic algorithms

Joghataie

Mohebbi

2012

Structural Design Tall Build

View full text Add to dashboard Cite

Active control of multi‐storey frame structures with nonlinear hysteretic response has been studied in this paper. A new nonlinear optimal control algorithm based on nonlinear Newmark integration method and distributed genetic algorithm (DGA) has been developed. The objective has been to reduce the response to below any desired level. In this study, DGA has been used to determine the weights in the control law corresponding to displacement, velocity and acceleration. The capabilities of the method has been assessed through simulation where an eight‐storey frame with bilinear hysteretic behaviour has been subjected to a white noise ground acceleration and controlled by the controllers designed by the new algorithm. An active tendon control system comprised of prestressed tendons and either a single actuator, which could apply a force to one of the floors, or eight actuators, which could fully control the frame, has been used. Also, the optimum actuator placement in the single actuator case has been studied. The designed controllers have been tested under both near and far‐field earthquakes and have performed successfully. Copyright © 2009 John Wiley & Sons, Ltd.

show abstract

Structural Optimization

MacBain¹,

Spillers²

2009

View full text Add to dashboard Cite

Multiple Optimum Size/Shape/Topology Designs for Skeletal Structures Using a Genetic Algorithm

Cited by 66 publications

References 22 publications

Harmony Search Method for Multimodal Size, Shape, and Topology Optimization of Structural Frameworks

Harmony Search Method for Multimodal Size, Shape, and Topology Optimization of Structural Frameworks

Optimal control of nonlinear frames by Newmark and distributed genetic algorithms

Structural Optimization

Contact Info

Product

Resources

About