Hybridizing extended ant lion optimizer with sine cosine algorithm approach for abrupt motion tracking

Zhang, Huanlong; Gao, Zeng; Zhang, Jie; Liu, Junfeng; Nie, Zhicheng; Zhang, Jianwei

doi:10.1186/s13640-020-0491-y

Cited by 10 publications

(9 citation statements)

References 53 publications

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“…The comparative simulations show that the SCA-DE can provide more robust tracking than the other trackers. Zhang et al (2020) proposed a hybrid extended ant lion optimizer (EALO) with a sine cosine algorithm (EALO-SCA) as a tracking algorithm through considering the abrupt motion. In this context, EALO is introduced with multiple elites rather than a single elite as in the standard ALO to improve the global exploration searches.…”

Section: Hybrid Sca Algorithmsmentioning

confidence: 99%

A comprehensive survey on the sine–cosine optimization algorithm

Rizk‐Allah

Hassanien

2022

Artif Intell Rev

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Metaheuristic algorithms based on intelligent rules have been successfully developed and applied to solve many optimization areas over the past few decades. The sine–cosine algorithm (SCA) imitates the behaviour of transcendental functions while the sine and cosine functions are presented to explore and exploit the search space. SCA starts by random population and executes iterative evolution processes to update the standard evolutionary algorithm’s destination or the best location. SCA used linear transition rules to balance the exploration and exploitation searches while searching for the best or optimal solutions. Since Mirjalili proposed it in 2016, SCA has attracted many researchers’ attention to deal with several optimization problems in many fields due to its strengths in solving optimization tasks that include the simple concept, easiness of implementation, and rapid convergence. This paper aims to provide researchers with a relatively comprehensive and extensive overview of the Sine–Cosine optimization algorithm in the literature to inspire further research. It examines the available publications, including improvements, binary, chaotic, hybridizations, multi-objective variants, and different applications. Some optimization formulations regarding single-objective optimization problems, multi-objective optimization problems, binary-objective optimization problems, and more classifications regarding the optimization types are discussed. An extensive bibliography is also included.

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Section: Hybrid Sca Algorithmsmentioning

confidence: 99%

A comprehensive survey on the sine–cosine optimization algorithm

Rizk‐Allah

Hassanien

2022

Artif Intell Rev

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“…( 2020 ) SCA + ALO EALO-SCA – Abrupt motion tracking Efficiency of EALO-SCA compared to other state-of-the-art optimization trackers Zhang et al. ( 2020 ) SCA + CSA SCCSA – Global optimization problems SCCSA gives competitive results in comparison with other state-of-the-art optimization algorithms Pasandideh and Khalilpourazari ( 2018 ) SCCSA – Power joint optimal scheduling dispatch Capability of SCCSA to control the voltage of nodes in micro-grid Ye et al. ( 2018 ) SCCSA Global optimization problems Superiority of SCCSA compared to other state-of-the-art optimization algorithms Khalilpourazari and Pasandideh ( 2019 ) SCA + SSA ISSAFD Feature selection ISSAFD provides better results compared to other well-regarded optimization techniques in terms of accuracy, sensitivity, and specificity Neggaz et al.…”

Section: Recent Variants Of the Sine Cosine Algorithmmentioning

confidence: 99%

“…Zhang et al. ( 2020 ) developed a hybrid approach, called EALO-SCA, based on the hybridization of SCA with Extended ALO (EALO) for abrupt motion tracking. EALO was integrated into SCA to enhance the global exploration ability.…”

Section: Recent Variants Of the Sine Cosine Algorithmmentioning

confidence: 99%

A comprehensive survey of sine cosine algorithm: variants and applications

et al. 2021

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Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions. Furthermore, the applications of SCA in several domains such as classification, image processing, robot path planning, scheduling, radial distribution networks, and other engineering problems are described. Finally, the paper recommended some potential future research directions for SCA.

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“… 2020 ), wireless sensor nodes localiser (Hamouda and Abohamama 2020 ), abrupt motion tracking (Zhang et al. 2020 ), optimal distributed generators allocation in radial distribution systems (Raut and Mishra 2020 ), nonlinear bilevel programming problems (Abo-Elnaga and El-Shorbagy 2020 ), traveling salesman problem (Tawhid and Savsani 2019 ), truss structures (Gholizadeh and Sojoudizadeh 2019 ), train multilayer perceptrons (Gupta and Deep 2020 ), parameter optimization of support vector regression (Li et al. 2018 ), text categorization (Belazzoug et al.…”

Section: Introductionmentioning

confidence: 99%

Economic load dispatch using memetic sine cosine algorithm

Al-Betar

Awadallah

Zitar

et al. 2022

J Ambient Intell Human Comput

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In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. Therefore, -hill climbing optimizer, a recent local search algorithm, is hybridized as a new operator in SCA to empower its exploitation capability to tackle ELD. The proposed hybrid algorithm is abbreviated as SCA- HC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. (ii) 6-units and 15-units with Ramp Rate Limits and Prohibited Operating Zones constraints. The sensitivity analysis of the control parameters for SCA- HC is initially studied. The results show that the performance of the SCA- HC algorithm is increased by tuning its parameters in proper value. The comparative evaluation against several state-of-the-art methods show that the proposed method is able to produce new best results for some tested cases as well as the second-best for others. In a nutshell, hybridizing HC optimizer as a new operator for SCA is very powerful algorithm for tackling ELD problems.

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Hybridizing extended ant lion optimizer with sine cosine algorithm approach for abrupt motion tracking

Cited by 10 publications

References 53 publications

A comprehensive survey on the sine–cosine optimization algorithm

A comprehensive survey on the sine–cosine optimization algorithm

A comprehensive survey of sine cosine algorithm: variants and applications

Economic load dispatch using memetic sine cosine algorithm

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