STSA: A sine Tree-Seed Algorithm for complex continuous optimization problems

Jiang, Jianhua; Xu, M.; Meng, Xianqiu; Li, Keqin

doi:10.1016/j.physa.2019.122802

Cited by 41 publications

(14 citation statements)

References 35 publications

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“…The ten experiment datasets are obtained from [30], whereas the characteristics of the selected datasets are presented in Table 1. In this experiment, MPGND is compared with many metaheuristics, including the original MPA, GNDO, Augmented Grey Wolf Optimizer (AGWO) [31], Sine Tree-Seed Algorithm (STSA) [32], Archimedes Optimization Algorithm (AOA) [33], and Student Psychology-Based Optimization (SPBO) [34] algorithm. The number of total search iterations of all algorithms is set to 500 while the population size is set to 30.…”

Section: Resultsmentioning

confidence: 99%

Green Communication for Sixth‐Generation Intent‐Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm

Eldrandaly

Abdel-Fatah

Abdel‐Basset

et al. 2021

Wireless Communications and Mobile Computing

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The sixth-generation (6G) is envisioned as a pivotal technology that will support the ubiquitous seamless connectivity of substantial networks. The main advantage of 6G technology is leveraging Artificial Intelligence (AI) techniques for handling its interoperable functions. The pairing of 6G networks and AI creates new needs for infrastructure, data preparation, and governance. Thus, Intent-Based Network (IBN) architecture is a key infrastructure for 6G technology. Usually, these networks are formed of several clusters for data gathering from various heterogeneities in devices. Therefore, an important problem is to find the minimum transmission power for each node in the network clusters. This paper presents hybridization between two Computational Intelligence (CI) algorithms called the Marine Predator Algorithm and the Generalized Normal Distribution Optimization (MPGND). The proposed algorithm is applied to save power consumption which is an important problem in sustainable green 6G-IBN. MPGND is compared with several recently proposed algorithms, including Augmented Grey Wolf Optimizer (AGWO), Sine Tree-Seed Algorithm (STSA), Archimedes Optimization Algorithm (AOA), and Student Psychology-Based Optimization (SPBO). The experimental results with the statistical analysis demonstrate the merits and highly competitive performance of the proposed algorithm.

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Section: Resultsmentioning

confidence: 99%

Green Communication for Sixth‐Generation Intent‐Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm

Eldrandaly

Abdel-Fatah

Abdel‐Basset

et al. 2021

Wireless Communications and Mobile Computing

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“…The STSA method is to improve the ability of the Tree-Seed Algorithm (TSA) based on the inspiration of the Sine Cosine algorithm (SCA). TSA has weaknesses in optimizing multimodal and high-order objective functions [20]. Seeds have an important role in the distribution and search for optimal value.…”

Section: A Sine Tree-seed Algorithm (Stsa)mentioning

confidence: 99%

“…Several artificial intelligence methods particularly the metaheuristic method have been used in solving ED problems in the past 5 years such as the chaotic bat algorithm (CBA) method which is a variant of the basic bat algorithm by entering chaotic sequences to improve its performance [4][5][6][7], Artificial Bee Colony Algorithm (ABC) which mimics the intelligent honeybee foraging behavior [8][9][10], grey wolf optimizer (GWO) inspired by hunting rules wolves and the grey wolf social hierarchy [11][12][13][14], and cuckoo search algorithm inspired by the interesting breeding behavior of cuckoo [15][16][17][18]. This paper will explore the potential of six metaheuristic methods, namely, Seagull Optimization Algorithm (SOA) [18], marine predator algorithm (MPA) [19], Sine Tree-Seed Algorithm (STSA) [20], Chimp Optimization Algorithm (ChOA) [21], Equilibrium Optimizer (EO) [22], and Giza Pyramids Construction (GPC) [23] in solving ELD problems. The test is using 2 different case studies and is based on several constraints.…”

Section: Introductionmentioning

confidence: 99%

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Aribowo

2022

Gazi University Journal of Science

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“…Where " " the objective function and "P" is the solutions which are suitable. Tree position has been taken into consideration where seeds are engendered and also it will be as most excellent location for the population of the trees [44][45][46][47]. Then the updating equation can be mathematically written as,…”

Section: Hybridization Of Tree-seed Algorithm With Sine-cosine Algorithmmentioning

confidence: 99%

Real Power Loss Reduction by Hybridization of Tree-Seed Algorithm with Sine-Cosine Algorithm

Lenin¹

2021

JEPES

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In this work, real power loss has done through hybridized Tree-seed algorithm. Sine-cosine algorithm which has been combined with Tree-seed algorithm (HTS) is projected to solve the problem. Tree-seed algorithm is based on the relationship between trees and seeds. And Sine Cosine Algorithm is based on the functions of Sine and Cosine; it stimulates the leader variable agent solutions towards the most excellent solution. In this work, seed engendering mechanism has been enhanced through adaptive mode and with reference to the iterations a linearly (k) varying mechanism has been implemented to perk up the exploration and exploitation. With considering voltage stability index proposed hybridized Tree-seed algorithm (HTS) is tested in IEEE 30, bus system. Then, the Proposed hybridized Tree-seed algorithm has been tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage stability index. In first analysis with considering voltage stability index real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained. In the second evaluation without considered voltage stability index, also power loss reduction achieved. Percentage of power loss reduction is 15.80%, 20.74%, 26.29%, and 14.55% with respect to the base value. Power Loss comparison has been done with other standard methods.

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STSA: A sine Tree-Seed Algorithm for complex continuous optimization problems

Cited by 41 publications

References 35 publications

Green Communication for Sixth‐Generation Intent‐Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm

Green Communication for Sixth‐Generation Intent‐Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm

Comparison Study On Economic Load Dispatch Using Metaheuristic Algorithm

Real Power Loss Reduction by Hybridization of Tree-Seed Algorithm with Sine-Cosine Algorithm

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