Optimisation of Engineering Systems With the Bees Algorithm

Pham, Duc Truong; Baronti, Luca; Zhang, Biao

doi:10.4018/ijalr.2018010101

Cited by 12 publications

(5 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BA was inspired by the pollen-seeking strategies of honey bees 27 . The search method of honey bees is based on sending more collectors to fertile pollen fields and sending fewer collectors to less fertile fields.…”

Section: Ba and Optimization Of The Springs Parametersmentioning

confidence: 99%

Optimization of spring parameters by using the Bees algorithm for the foldable wing mechanism

Şahin

Kulunk

2022

Sci Rep

View full text Add to dashboard Cite

In this study, the design of the torsion and compression springs of the foldable wing mechanism used in the missile is considered an optimization problem. After the missile leaves the tube, the wings waiting in a closed state must be opened and fixed within a specific time. The study it is aimed to maximize the energy stored by the springs so that the wing can be opened in a minimum time. In this context, the energy equation in both publications is defined as the objective function in the optimization process. Wire diameter, coiling diameter, coiling number, and deflection parameters required for spring design were determined as optimization variables. There are geometrical constraints for the variables due to the dimensions of the mechanism and there are also safety factor constraints due to the loads to which the springs are exposed. The Bees Algorithm (BA) was used to solve this optimization problem and perform the spring design. The energy values obtained with BA were better than the values obtained with the Design of Experiment (DOE) study before. The springs and mechanism designed with the parameters obtained from the optimization were first analyzed in the ADAMS program. Afterward, experimental tests carried out by integrating the produced springs into the actual mechanism. As a result of the tests, it was observed that the wing opened at approximately 90 ms. This value is well below the project target of 200 ms. In addition, there is only a 16 ms difference between the analysis and the experimental results.

show abstract

Section: Ba and Optimization Of The Springs Parametersmentioning

confidence: 99%

Optimization of spring parameters by using the Bees algorithm for the foldable wing mechanism

Şahin

Kulunk

2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…If the shrinking procedure brings no improvement in the fitness value in a given neighborhood after a predefined number of iterations. It is assumed that the local optimum has been reached [36]. Therefore, the solution is replaced with a new one using the MCSA algorithm.…”

Section: Site Abandonmentmentioning

confidence: 99%

Hybrid Algorithm for Node Deployment with the Guarantee of Connectivity in Wireless Sensor Networks

Deghbouch

Debbat

2022

IJCAI

View full text Add to dashboard Cite

In this paper, the problem of deployment in wireless sensor networks is investigated. The authors propose a Hybrid Modified Crow Search Bee Algorithm (HMCSBA) for coverage maximization with the guarantee of connectivity between the deployed sensors. Firstly, a Modified Crow Search Algorithm (MCSA) is proposed based on the basic CSA algorithm to form a connected network after initial random deployment. The position equation of the original CSA was updated by introducing a linear flight length that increases throughout iterations to force the sensors to join the network. Then, the Bees Algorithm (BA) is applied to optimize the network coverage without losing connectivity between the deployed sensors. Simulations and comparative studies were carried out to prove the relevance of the proposed algorithm. Results demonstrate that the proposed algorithm can optimize the coverage and guarantee network connectivity.Povzetek: Razvit je bil hibridni algoritem HMCSBA za zagotovljeno povezljivost brezžičnih senzorjev v omrežju.

show abstract

“…For the calculation of switching angles in multilevel inverter, this evolutionary algorithm based on foraging act of bees in nature is implemented [28]. Naturally three types of bees are considered in bees swarm; employed bees, on-looker bees and scout bees.…”

Section: Proposed Genetic (Ga) Algorithmmentioning

confidence: 99%

Selective Harmonics Elimination in Multilevel Inverter Using Bio-Inspired Intelligent Algorithms

Shahbaz

Ahmed

Elavarasan³

et al. 2021

2021 31st Australasian Universities Power Engineering Conference (AUPEC)

View full text Add to dashboard Cite

Multilevel inverters are powerful electronic devices that are used for the conversion of DC input voltage into AC output voltage and mostly used in medium and high voltage operations. In these operations, pulse width modulation (PWM) frequency is distorted because of electromagnetic interference (EMI) and switching losses which are caused by dv/dt stress. To achieve a pure sinusoidal waveform at output of multilevel inverter is a primary purpose so that a smaller number of harmonic contents are produced. Selective harmonic elimination PWM technique is used in cascaded multilevel inverter for the mitigation of lower harmonics by solving nonlinear transcendental equations and maintains the required fundamental voltage. An objective function is derived from SHE problem to calculate switching angles. For the solution of objective function, optimization approach such as bio-inspired intelligent algorithms are used. In this paper, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Bee Algorithm (BA) are used to determine the optimum switching angles for cascaded multilevel inverters to get low total harmonic distortion (THD) in output voltage. These computed angles are analyzed in MATLAB simulation model to authenticate the results. And there will be direct comparison among these algorithms.

show abstract

Optimisation of Engineering Systems With the Bees Algorithm

Cited by 12 publications

References 47 publications

Optimization of spring parameters by using the Bees algorithm for the foldable wing mechanism

Optimization of spring parameters by using the Bees algorithm for the foldable wing mechanism

Hybrid Algorithm for Node Deployment with the Guarantee of Connectivity in Wireless Sensor Networks

Selective Harmonics Elimination in Multilevel Inverter Using Bio-Inspired Intelligent Algorithms

Contact Info

Product

Resources

About