Optimization of laminate stacking sequence for minimizing weight and cost using elitist ant system optimization

Hemmatian, Hossein; Fereidoon, Abdolhossein; Sadollah, Ali; Bahreininejad, Ardeshir

doi:10.1016/j.advengsoft.2012.11.005

Cited by 40 publications

(18 citation statements)

References 16 publications

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“…This system is to strength the searching in an ant system [4]. This system includes the procedures such as diversification and intensification techniques.…”

Section: Elitist Ant Systemmentioning

confidence: 99%

A hybrid ACO-PSO based clustering protocol in VANET

Amudhavel¹,

Kumar²,

Monica³

et al. 2015

Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering &Amp; Technology (ICARCSE

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VANET means vehicular ad-hoc network. The routing protocol ant colony optimization (ACO) is a swarm intelligence which is based on the behavior of the ant, the ACO algorithm includes the cooperation and adaption and it produces an optimal solution.ACOalgorithm depends upon the amount of pheromone deposit. The particle swarm optimization is also swarm intelligence, the PSO algorithm is population based and depends upon the movement and the intelligence of the swarm. The pheromone value is used for the decision purpose. The benefit of particle swarm optimization technique is that the particle moves always in the same direction with the same velocity and it also selects the position that is better than the previous position thus the best path is followed by each particle. In PSO the set of potential solutions evolves to approach a convenient solution for a problem. This algorithm produces Global best (Gbest) and Personal best (Pbest) solution. The benefits of the ACO and PSO protocols are combine have a hybridACO-PSOalgorithm to have an optimal solution to a multicast network and thus it helps in clustering.

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“…This system is to strength the searching in an ant system [4]. This system includes the procedures such as diversification and intensification techniques.…”

Section: Elitist Ant Systemmentioning

confidence: 99%

A hybrid ACO-PSO based clustering protocol in VANET

Amudhavel¹,

Kumar²,

Monica³

et al. 2015

Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering &Amp; Technology (ICARCSE

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“…The weight is thus calculated by the following formula [19]: (9) For example, g (g = 9.8 m/s2) is the constant of gravity. The Pareto-optimal set represents the set of non-dominated solutions defined for a multi-objective optimization problem [20].…”

Section: Optimizationof Laminated Composite Platesmentioning

confidence: 99%

Artificial Intelligence Approach for Multi-Objective Design Optimization of Composite Structures: Parallel Genetic Immigration

Majdoubi¹

2020

IJATCSE

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An isotropic mechanical structure cannot withstand shocks, accidents, and mechanical loading. In this perspective, composite structures have been introduced to improve the performance of mechanical structures. We are interested in the study of laminates with the aim to find an optimal structure resistant to vibrations and buckling. To remedy the problem of vibrations and buckling, we use artificial intelligence methods to optimize the design of composite structures. As it is a typical method of artificial intelligence adapted to this studied problem, we use genetic algorithms based on a new genetic operator. In the present article, an optimization procedure based on the new genetic operator called genetic immigration operator is developed to determine the maximum buckling load and fundamental frequency of the laminated plate with plies oriented at -45•/45• ,0•, and 90•. The aim of this paper is the use of two different methods for their effectiveness. These optimization works consist of first maximizing the buckling load factor with UGA (Uniform Genetic Algorithm) and a new evolutionary search strategies called Immigration Genetic: SIG (Standard Immigration Genetic Algorithm) and AIG (Improved Genetic Immigration Algorithm) and second of solving a multi-objective problem with minimizing the cost and weight of the hybrid laminate made of the fibers of two composite materials. The resolution of this problem by the proposed genetic immigration approach is reinforced by the optimization of the CPU computation time which is due to the exploitation of the parallel architecture based on the multi-processor parallel computation.

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“…To retain the strengths of single-platform systems while reducing their weaknesses, there is need to combine and optimize them (Popovic, Hackney, Coelho & Jaklic, 2012). These can be done through hybridizing the single-platform systems, through which these strengths and weaknesses can be selectively addressed (Hemmatian, Fereidoon, Sadollah, & Bahreininejad, 2013;Zhang, Wang, Dong, Phillip, Ji, & Yang, 2015). Therefore, to deploy the proposed system, the researcher intends to hybridize three (3) single-platforms namely -the standalone platform for offline deployment, with the private-cloud and public-cloud platforms, for online deployment.…”

Section: The Platform Optimizationmentioning

confidence: 99%

Multivariate Analysis of Performance of Hybrid Result System Model for Nigerian Universities

Etus¹,

Eheduru²,

Eze³

et al. 2019

theijst

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processing and management of students' results involve many complex stages (Okebukola, 2010). As more information are made available in a variety of formats and sources, processing and management of data becomes more and more complex, which can be handled using Information System approach (Oliveira, Thomas & Espadanal, 2014). Despite the proliferation of vendor result processing and management systems, the automation level of the existing singleplatform system models prevalent in Nigerian Universities are unsatisfactory. The existing single-platform systems are the completely offline (standalone) system and the completely online (client-server) system, which can be web-based or application-based (

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Optimization of laminate stacking sequence for minimizing weight and cost using elitist ant system optimization

Cited by 40 publications

References 16 publications

A hybrid ACO-PSO based clustering protocol in VANET

A hybrid ACO-PSO based clustering protocol in VANET

Artificial Intelligence Approach for Multi-Objective Design Optimization of Composite Structures: Parallel Genetic Immigration

Multivariate Analysis of Performance of Hybrid Result System Model for Nigerian Universities

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