A hybrid real-parameter genetic algorithm for function optimization

Hwang, Shun‐Fa; He, Rong-Song

doi:10.1016/j.aei.2005.09.001

Cited by 187 publications

(71 citation statements)

References 26 publications

(38 reference statements)

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“…Thus, an identification method combining experiment design, the response-surface function, and finite element analysis has been used for the elastic constants of composite laminates Ma et al 1999). The works of Cunha, Maletta, Hwang, and Lee clearly show the potential of genetic algorithms (GAs) for the procedure of identifying material properties (Cunha et al 1997;Hwang et al 2006;Lee et al 2006). Also, some special techniques can enhance the GAs, e.g., Hwang uses a hybrid real parameter GA (RGA) for inverse determination.…”

Section: Identification Proceduresmentioning

confidence: 99%

“…Also, some special techniques can enhance the GAs, e.g., Hwang uses a hybrid real parameter GA (RGA) for inverse determination. RGA overcomes parameter encoding and decoding and saves computational time (Hwang 2000;Hwang et al 2006;Hwang 2006).…”

Section: Identification Proceduresmentioning

confidence: 99%

“…Vibration testing combined with a numerical method is a potential alternative approach to determine the elastic constants of materials because of its non-destructive character, single test, and ability to produce average properties (Ayorinde et al 1993;Ayorinde 1995; Hwang et al 2006).…”

Section: Introductionmentioning

confidence: 99%

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Identification of Material Properties of Composite Materials

Ragauskas

Belevičius

2009

Aviation

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Abstract. Present paper describes the facilities of composite material properties identification technique using specimen vibration tests, genetic algorithms, finite elements analysis and specimen shape optimization. In identification process the elastic constants in a numerical model is updated so that the output from the numerical code fits the results from vibration testing. Main problem analysed in this paper is that Poisson's ratio is the worst determined elastic characteristic due to its low influence on specimen eigenfrequencies. It is shown that it is possible to increase its influence by choosing specific test specimen characteristics (side aspect ratio, orthotropy angle, etc.) via optimization routine. In this paper are presented test results of some experiments wherein glass-epoxy and carbonepoxy material properties were identified.

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Section: Identification Proceduresmentioning

confidence: 99%

Section: Identification Proceduresmentioning

confidence: 99%

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Identification of Material Properties of Composite Materials

Ragauskas

Belevičius

2009

Aviation

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“…Along with the developing of optimization theory and technologies, the integrated scheduling of handling equipment is receiving increasing attention in academe and industry. However, after reviewing previous related research [6][7][8][9][10][11][12] , we find that the existing integrated YC and YT scheduling optimizing research all based on work line strategy, which is difficult to satisfy the need of increasingly busy production activities in container terminals. Facing the existed problem, this paper proposed an integrated YC and YT scheduling optimization model based on pool strategy to minimize the makespan of loading operation.…”

Section: Introductionmentioning

confidence: 99%

Integrated Scheduling Optimization of Yard Crane and Yard Truck in Ship-loading Operation

Cao¹,

Jiang²,

Zhao³

2017

Proceedings of the 2017 2nd International Conference on Civil, Transportation and Environmental Engineering (ICCTE 2017)

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Abstract.To further decrease turnaround time of container vessels, synchronous operation of Quay Cranes (QCs), Yard Cranes (YCs) and Yard Truck (YTs) is mainly considered in multiple work lines condition and an integrated scheduling optimization model of YC and YT, aiming at minimize the makespan of loading operation, is proposed with the consideration of practical constrains. According to complexity of the mathematical model, the multi-layers genetic algorithm (MLGA) is introduced to allocate the tasks of QCs and YCs and FCFS rule is used to dispatch YTs. Additionally, a YC dynamic scheduling strategy is proposed to further improve the solving efficiency of MLGA. In the end, effectiveness of the model and algorithm is certified by making numerical experiments.

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“…Another approach consists in the joint (hybrid) use of different optimizers, such as PSO, ACO, GA, etc., in the same platform through swarms that share all the resources in a multi-agent structure. There are numerous examples in the literature of multiple optimizers being used together (Onwubolu and Babu, 2004;Javadi, Farmani, and Tan, 2005;Hwang and He, 2006;Vrugt and Robinson, 2007;Shang, Zhao, and Shen, 2009). The proposal in this article considers hybridization of heuristics of different nature within a joint multi-agent based platform (Montalvo et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A hybrid, auto-adaptive and rule-based multi-agent approach using evolutionary algorithms for improved searching

Izquierdo

Montalvo²,

Campbell

et al. 2015

Engineering Optimization

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Izquierdo Sebastián, J.; Montalvo Arango, I.; Campbell, E.; Pérez García, R. (2015). A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching. Engineering Optimization. 1-13. doi:10.1080/0305215X.2015.1107434.A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching Selecting the most appropriate heuristic for solving a specific problem is not easy. The reasons are manifold. This article focus on one of these reasons: traditionally, the solution search process has operated in a given manner regardless of the specific problem being solved, and the process has been the same no matter the size, complexity, and domain of the problem. To cope with this situation, search processes should mould the search into areas of the search space that are meaningful for the problem. This article builds on previous work in the development of a multi-agent paradigm through the use of techniques derived from knowledge discovery (data mining techniques) on databases of so-far visited solutions. The aim is to improve search mechanisms, increase computational efficiency, and enrich through rules the formulation of optimization problems -while reducing the search space and catering to realistic problems.

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A hybrid real-parameter genetic algorithm for function optimization

Cited by 187 publications

References 26 publications

Identification of Material Properties of Composite Materials

Identification of Material Properties of Composite Materials

Integrated Scheduling Optimization of Yard Crane and Yard Truck in Ship-loading Operation

A hybrid, auto-adaptive and rule-based multi-agent approach using evolutionary algorithms for improved searching

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