Modified Adaptive Bats Sonar Algorithm with Doppler Effect Mechanism for Solving Single Objective Unconstrained Optimization Problems

Azlan, Nor Asmaa Alyaa Nor; Yahya, Nafrizuan Mat

doi:10.1109/cspa.2019.8696057

Cited by 8 publications

(2 citation statements)

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“…Some recent techniques that can be used to solve this kind of problems are the Jaya algorithm [33], the Proactive Particles in Swarm Optimization (PPSO) [34], the Hybrid Population-Based Mean-Variance Mapping Optimization (MVMO-PH) [35], the Successful-History based Adaptative Differential Evolution with Linear size reduction and four adaptation strategies with Improved ε constraint-handling method (LSHADE44-IEpsilon) [36], the Hunting Optimization (HO) [37], and the Modified Adaptative Bats Sonar Algorithm with Doppler Effect (MABSA-DE) [38].…”

Section: Multiobjective Optimization Applied To Control Engineeringmentioning

confidence: 99%

A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach

et al. 2020

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In control engineering education, the possibility of using a real control system in the learning process motivates professors to improve both students’ knowledge and skills, thus avoiding an approach only based on control theory. While considering that control engineering laboratories are expensive, mainly because educational plants should reproduce classical problems that are found in the industry, the use of virtual laboratories appears as an interesting strategy for reducing costs and improving the diversity of experiments. In this research, remote experimentation was assumed regarding the ball and beam process as an alternative didactic methodology. While assuming a nonlinear and unstable open-loop process, this study presents how students should proceed to control the plant focusing on the topic that is associated with multiobjective optimization. Proportional-Integral-Derivative (PID) controller was tuned considering the Non-dominated Sorting Genetic Algorithm (NSGA-II) to illustrate the WebLab learning procedures described in this research. The proposed strategy was compared to the Åström’s robust loop shaping method to emphasize the performance of the multiobjective optimization technique. Analyzing the feedback provided by the students, remote experimentation can be seen as an interesting approach for the future of engineering learning, once it can be directly associated with industry demand of connected machines and real-time information analysis.

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Section: Multiobjective Optimization Applied To Control Engineeringmentioning

confidence: 99%

A Generic WebLab Control Tuning Experience Using the Ball and Beam Process and Multiobjective Optimization Approach

et al. 2020

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“…In 2010, Yang and his co-workers proposed BA (bat algorithm), which is a metaheuristic algorithm. Bat uses echolocation in the dark environment to locate their nest, detect the prey, and avoid obstacles [18]. BA algorithm does not stop until they find a suitable solution.…”

Section: Ba (Bat Algorithm)mentioning

confidence: 99%

December 2020

2020

JSCP

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Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) and BA (bat algorithm). The LSA algorithm helps the system to be faster, and BA algorithm helps to increase the accuracy of the system. This optimization algorithm is checked using MATLAB R2018b. Simulated using ModelSim, and the synthesizing is done using Xilinx Vivado 18.2 synthesis tool. The outcome of the simulation result and the synthesis result outshine other metaheuristic optimization algorithms.

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