Opposition based Laplacian Ant Lion Optimizer

Dinkar, Shail Kumar; Deep, Kusum

doi:10.1016/j.jocs.2017.10.007

Cited by 58 publications

(13 citation statements)

References 23 publications

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“…Boxplot analysis is a graphical method to compare the data distribution of sample data of objective function values taken from parent FA and the proposed model FA3 for each individual run. To analyze the empirical distribution of sample data very efficiently, this tool proven its importance . This visualization method is used to show 2 common measures of the sample data set namely first one is “Range”, which is denoted on a boxplot figure by the vertical distance between lowest and highest value of sample data taken and second one is, “Interquartile range (IQR)” which is measured through the width of box.…”

Section: Analytical Resultsmentioning

confidence: 99%

“…To analyze the empirical distribution of sample data very efficiently, this tool proven its importance. 31,32 This visualization method is used to show 2 common measures of the sample data set namely first one is "Range", which is denoted on a boxplot figure by the vertical distance between lowest and highest value of sample data taken and second one is, "Interquartile range (IQR)" which is measured through the width of box. For functions F1, F2, F9-F11 and F19, 6 boxplots have been drawn to validate and analyze the distribution of data for objective function values of unimodal, multimodal and fixed dimension multimodal respectively.…”

Section: Box Plot Analysismentioning

confidence: 99%

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A new redefined model of Firefly Algorithm with application to strategic bidding problem in Power Sector

Jain¹,

Saxena²

2020

Int Trans Electr Energ Syst

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Real‐life optimization problems require an effective mechanism that completely utilizes the search space to obtain optimal solutions. A designer has always an opportunity to propose a new effective solution technique to address this issue. In this order, this paper presents a new upgraded redefined model of nature‐inspired state of art meta‐heuristic firefly algorithm (FA). FA is centered on swarm intelligence, which is motivated by the flashing pattern and behavior of fireflies. However, for a few instances, FA has a tendency to trap in local optima and it exhibits slow convergence. The proposed model is enabled through Time‐varying Inertia Weight (TIW), Opposition Based Learning (OBL) and hybridized with sine cosine operators to get updated positions of search agents. A set of twenty‐two classical benchmark function problems with numerous range and features are employed to prove the efficacy of the proposed model. Also, the effects of the above‐mentioned modifications during the whole optimization routine are analyzed through different statistical and numerical analyses. The result analysis proves that the proposed modifications make FA more compatible. The proposed model is also tested on the strategic bidding problem of the power market of two different test systems with single and multi‐trading hours. All the reported results confirm the supremacy of the proposed redefined model of FA.

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Section: Analytical Resultsmentioning

confidence: 99%

Section: Box Plot Analysismentioning

confidence: 99%

A new redefined model of Firefly Algorithm with application to strategic bidding problem in Power Sector

Jain¹,

Saxena²

2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…The same authors in [132] proposed another version called OB-L-ALO to accelerate and enhance the native ALO by using 2 strategies: Laplace distribution is employed in random walk rather than uniform distribution besides OBL. They test the proposed algorithm using 27 benchmark function and give a comprehensive analysis of convergence curve, trajectories and data distribution using boxplot.…”

Section: ) Lévy Alo and Opposition-based Alomentioning

confidence: 99%

Ant Lion Optimization: Variants, Hybrids, and Applications

2020

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Ant Lion Optimizer (ALO) is a recent novel algorithm developed in the literature that simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge number of optimization problems. It has many advantages: easy, scalable, flexible, and have a great balance between exploration and exploitation. In this comprehensive study, many publications using ALO have been collected and summarized. Firstly, we introduce an introduction about ALO. Secondly, we categorized the recent versions of ALO into 3 Categories mainly Modified, Hybrid and Multi-Objective. we also introduce the applications in which ALO has been applied such as power, Machine Learning, Image processing problems, Civil Engineering, Medical, etc. The review paper is ended by giving a conclusion of the main ALO foundations and providing some suggestions & possible future directions that can be investigated.

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“…S.K. Dinkar and K. Deep presented an opposition Laplacian ALO for Gear Train Design and Capacity of Gas Production Facilities [41]. In [42], the authors have proposed a modified version of the ALO based on the chaotic mapping approach to recognize and State of Charge evaluation of NMC Cells.…”

Section: Introduction a Literature Surveymentioning

confidence: 99%

Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and DSTATCOM Under Uncertainties of Loads and Solar Irradiance

et al. 2021

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Optimal planning of integration the Photovoltage Distributed Generation (PV-DG) and DSTATCOM is a crucial task due to the stochastic variations of PV output power and the load demand which are related to solar irradiance variations and the activities of the customers, respectively. In this article, the optimal planning problem of the PV-DG and DSTATCOM system is solved. The proposed model considers the uncertainties of the solar irradiance and the load demand for a multi-objective function, including the cost reduction, the voltage profile, and stability index improvement. Modified Ant Lion Optimizer (MALO) is proposed to enhance the basic ALO searching ability using two strategies. The first strategy is based on Levy Flight Distribution (LFD) to strengthen the exploration of the algorithm and avoid the premature of the basic ALO. In contrast, the second strategy is based on updating the solutions in a spiral orientation to improve the exploitation of the algorithm. The IEEE 69-bus and 118-bus radial distribution systems are used to demonstrate the effectiveness of the proposed method, and the yielded simulations are compared with the basic ALO and other well-known optimization techniques for power loss minimization under deterministic conditions. The simulation results demonstrate that the techno-economic benefits can be increased considerably by optimal inclusion of two PV-DGs and DSTATCOMs compared with a single system.

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Opposition based Laplacian Ant Lion Optimizer

Cited by 58 publications

References 23 publications

A new redefined model of Firefly Algorithm with application to strategic bidding problem in Power Sector

A new redefined model of Firefly Algorithm with application to strategic bidding problem in Power Sector

Ant Lion Optimization: Variants, Hybrids, and Applications

Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and DSTATCOM Under Uncertainties of Loads and Solar Irradiance

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