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Journal articles on the topic 'Salp swarm optimization'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Castelli, Mauro, Luca Manzoni, Luca Mariot, Marco S. Nobile, and Andrea Tangherloni. "Salp Swarm Optimization: A critical review." Expert Systems with Applications 189 (March 2022): 116029. http://dx.doi.org/10.1016/j.eswa.2021.116029.

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Kulhari, Ankur, and Anil Saroliya. "Lévy-inspired Salp Swarm Optimization Algorithm." Procedia Computer Science 260 (2025): 796–804. https://doi.org/10.1016/j.procs.2025.03.260.

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3

Chabane, Djabali, and Bouktir Tarek. "SIMULTANEOUS ALLOCATION OF MULTIPLE DISTRIBUTED GENERATION AND CAPACITORS IN RADIAL NETWORK USING GENETIC-SALP SWARM ALGORITHM." Electrical engineering & electromechanics, no. 4 (August 21, 2020): 59–66. https://doi.org/10.20998/2074-272X.2020.4.08.

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<strong><em>Purpose. In recent years, the problem of allocation of distributed generation and capacitors banks has received special attention from many utilities and researchers. The present paper deals with single and simultaneous placement of dispersed generation and capacitors banks in radial distribution network with different load levels: light, medium and peak using genetic-salp swarm algorithm. The developed genetic-salp swarm algorithm (GA-SSA) hybrid optimization takes the system input variables of radial distribution network to find the optimal solutions to maximize the benefits of t

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Yıldız, Ali Rıza, and Mehmet Umut Erdaş. "A new Hybrid Taguchi-salp swarm optimization algorithm for the robust design of real-world engineering problems." Materials Testing 63, no. 2 (2021): 157–62. http://dx.doi.org/10.1515/mt-2020-0022.

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Abstract In this paper, a new hybrid Taguchi salp swarm algorithm (HTSSA) has been developed to speed up the optimization processes of structural design problems in industry and to approach a global optimum solution. The design problem is posed for the shape optimization of a seat bracket with a mass objective function and a stress constraint. Objective function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations necessary for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, gras

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Fan, Yuqi, Junpeng Shao, Guitao Sun, and Xuan Shao. "A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems." Complexity 2020 (November 18, 2020): 1–17. http://dx.doi.org/10.1155/2020/6371085.

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Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to the basic salp swarm algo

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Somasundaram, Deepa, Sasikala Arumugham, Puviarasi Ramalingam, Kirubakaran Dhandapani, and Kalaivani Ramaiyan. "Optimal fuzzy controller for speed control of DC drive using salp swarm algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1951. http://dx.doi.org/10.11591/ijpeds.v15.i3.pp1951-1958.

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The inherent non-linearity of the system being investigated highlights the limitations of traditional proportional integral or PI tuning approaches. Consequently, the primary objective of this study is to construct and refine the PI controller by leveraging the salp swarm algorithm, aiming to enhance the performance of the DC drive output. Through the application of the salp swarm algorithm, the fuzzy PI controller undergoes dynamic online modifications, leading to optimal results. The controller's superior performance is achieved by employing an optimization approach to identify the optimal s

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Somasundaram, Deepa, Sasikala Arumugham, Puviarasi Ramalingam, Kirubakaran Dhandapani, and Kalaivani Ramaiyan. "Optimal fuzzy controller for speed control of DC drive using salp swarm algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1951–58. https://doi.org/10.11591/ijpeds.v15.i3.pp1951-1958.

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The inherent non-linearity of the system being investigated highlights the limitations of traditional proportional integral or PI tuning approaches. Consequently, the primary objective of this study is to construct and refine the PI controller by leveraging the salp swarm algorithm, aiming to enhance the performance of the DC drive output. Through the application of the salp swarm algorithm, the fuzzy PI controller undergoes dynamic online modifications, leading to optimal results. The controller's superior performance is achieved by employing an optimization approach to identify the optimal s

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8

Duan, Qing, Lu Wang, Hongwei Kang, Yong Shen, Xingping Sun, and Qingyi Chen. "Improved Salp Swarm Algorithm with Simulated Annealing for Solving Engineering Optimization Problems." Symmetry 13, no. 6 (2021): 1092. http://dx.doi.org/10.3390/sym13061092.

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Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth balance between exploration and exploitation. Salp swarm algorithm(SSA), as a swarm-based algorithm on account of the predation behavior of the salp, can solve complex daily life optimization problems in nature. SSA also has the problems of local stagnation and slow convergence rate. This paper introduces an improved salp swarm algorithm, which improve the SSA by using the chaotic sequence initialization strategy and symmetric adaptive population division. Moreover, a simulated annealing mechani

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Cheruiyot, Fabian, and Davies Segera. "A Master-Slave Salp Swarm Algorithm Optimizer for Hybrid Energy Storage System Control Strategy in Electric Vehicles." Journal of Energy 2022 (September 14, 2022): 1–20. http://dx.doi.org/10.1155/2022/1648433.

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Pure electric vehicles provide an enticing ecofriendly alternative to traditional fossil fuel combustion engine locomotives. Batteries have primarily been used to store energy in electric vehicles; however, peak load demand and transient power leading to decreased battery lifespan have bred interest in hybrid energy storage systems in electric vehicles. Management of energy drawn from a hybrid energy storage system (HESS) in electric vehicles is a real-time multistage optimization problem aimed at minimizing energy consumption while aptly distributing energy drawn from the battery and capacito

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Yang, Heng, Yuhang Ren, and Gening Xu. "Optimization of Rotary Drilling Rig Mast Structure Based on Multi-Dimensional Improved Salp Swarm Algorithm." Applied Sciences 14, no. 21 (2024): 10040. http://dx.doi.org/10.3390/app142110040.

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The mast is a critical component of rotary drilling rigs, which has a cross-section consisting of a rectangular shape formed by two web plates and two flange plates. Structural optimization of the mast is necessary to address the issue of excessive weight. The shortcomings of the traditional structural optimization algorithms are summarized as follows: the optimized steel plate thickness is a non-integer, where rounding upwards may increase the cost to a certain extent, but it can ensure the safety of the structure; rounding downwards its load carrying capacity may not satisfy the requirements

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11

Lu, Jing, XiaoBo Su, Jingyu Zhong, and Gang Hu. "Enhanced Salp Swarm Algorithm for Optimizing the Shape of Developable Bézier-Like Surfaces." Mathematical Problems in Engineering 2022 (August 30, 2022): 1–30. http://dx.doi.org/10.1155/2022/1796642.

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The shape optimization of developable surfaces is a key and difficult technology in CAD/CAM. This paper studies the shape optimization of generalized developable Bézier-like surfaces using the improved salp swarm algorithm. First, aiming at the problems of slow convergence speed and low calculation accuracy, quickly falling into the optimal local solution for the salp swarm algorithm, and by adjusting the control parameters, the added Morlet wavelet mutation strategy to the individual position updates operation. An improved salp swarm algorithm is proposed, called FMSSA for short. Numerical re

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Deng, Liwei, Shanshan Liu, Xiaofei Wang, Guofu Zhao, and Jiazhong Xu. "Particle Swarm Optimization and Salp Swarm Algorithm for the Segmentation of Diabetic Retinal Blood Vessel Images." Computational Intelligence and Neuroscience 2022 (August 23, 2022): 1–14. http://dx.doi.org/10.1155/2022/1936482.

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In recent years, the incidence of diabetes has been increasing year by year. Since most of the fundus lesions are located near blood vessels, the image information is complex, and the end vessels are difficult to identify. So, a new segmentation method of diabetic retinal vessel images based on particle swarm optimization and salp swarm algorithm is proposed. This paper uses a Gaussian filter to enhance the main blood vessels, and a top-bot hat transform is used to strengthen the end vessels. The preprocessing process is completed by combining and reconstructing the two images through a normal

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Manikandan, K., and B. Sudhakar. "Hybrid Optimization Algorithm for Multi-level Image Thresholding Using Salp Swarm Optimization Algorithm and Ant Colony Optimization." International Journal of Electrical and Electronic Engineering & Telecommunications 12, no. 6 (2023): 411–23. http://dx.doi.org/10.18178/ijeetc.12.6.411-423.

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The process of identifying optimal threshold for multi-level thresholding in image segmentation is a challenging process. An efficient optimization algorithm is required to find the optimal threshold and various nature inspired; evolutionary optimization algorithms are presented by the research community. However, to improve the performance in finding optimal threshold value and minimize the error, reduces the searching time a hybrid optimization algorithm is presented in this research work using salp swarm optimization and ant colony optimization algorithm. The ant colony optimization algorit

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Kurt, Erhan, Suad Basbug, and Kerim Guney. "Sidelobe level suppression for elliptical antenna arrays using modified SALP swarm algorithm." Journal of Electrical Engineering 73, no. 5 (2022): 325–31. http://dx.doi.org/10.2478/jee-2022-0043.

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Abstract In this study, a modified version of salp swarm algorithm (MSSA) is used to synthesize elliptical antenna arrays (EAAs). The original salp swarm algorithm (SSA) is an optimization algorithm inspired by the behavior of salps in nature, which is used to solve engineering problems. The main purpose of the synthesis in this study is to obtain an EAA pattern with low maximum sidelobe levels (MSLs) for a fixed narrow first null beamwidth (FNBW). For different examples, the amplitude and angular position values of the antenna array elements are considered as optimization parameters. To show

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15

Jia, Heming, and Chunbo Lang. "Salp swarm algorithm with crossover scheme and Lévy flight for global optimization." Journal of Intelligent & Fuzzy Systems 40, no. 5 (2021): 9277–88. http://dx.doi.org/10.3233/jifs-201737.

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Salp swarm algorithm (SSA) is a meta-heuristic algorithm proposed in recent years, which shows certain advantages in solving some optimization tasks. However, with the increasing difficulty of solving the problem (e.g. multi-modal, high-dimensional), the convergence accuracy and stability of SSA algorithm decrease. In order to overcome the drawbacks, salp swarm algorithm with crossover scheme and Lévy flight (SSACL) is proposed. The crossover scheme and Lévy flight strategy are used to improve the movement patterns of salp leader and followers, respectively. Experiments have been conducted on

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Dahiya, Brahm Prakash, Shaveta Rani, and Paramjeet Singh. "A Hybrid Artificial Grasshopper Optimization (HAGOA) Meta-Heuristic Approach: A Hybrid Optimizer For Discover the Global Optimum in Given Search Space." International Journal of Mathematical, Engineering and Management Sciences 4, no. 2 (2019): 471–88. http://dx.doi.org/10.33889/ijmems.2019.4.2-039.

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Meta-heuristic algorithms are used to get optimal solutions in different engineering branches. Here four types of meta-heuristics algorithms are used such as evolutionary algorithms, swarm-based algorithms, physics based algorithms and human based algorithms respectively. Swarm based meta-heuristic algorithms are given more effective result in optimization problem issues and these are generated global optimal solution. Existing swarm intelligence techniques are suffered with poor exploitation and exploration in given search space. Therefore, in this paper Hybrid Artificial Grasshopper Optimiza

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Ibrahim, Rehab Ali, Ahmed A. Ewees, Diego Oliva, Mohamed Abd Elaziz, and Songfeng Lu. "Improved salp swarm algorithm based on particle swarm optimization for feature selection." Journal of Ambient Intelligence and Humanized Computing 10, no. 8 (2018): 3155–69. http://dx.doi.org/10.1007/s12652-018-1031-9.

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Song, Jiuman, Chengcheng Chen, Ali Asghar Heidari, Jiawen Liu, Helong Yu, and Huiling Chen. "Performance optimization of annealing salp swarm algorithm: frameworks and applications for engineering design." Journal of Computational Design and Engineering 9, no. 2 (2022): 633–69. http://dx.doi.org/10.1093/jcde/qwac021.

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Abstract Swarm salp algorithm is a swarm intelligence optimization algorithm enlightened by the movement and foraging behaviors of the salp population. The salp swarm algorithm (SSA) has a simple structure and fast processing speed and can gain significant results on objective functions with fewer local optima. However, it has poor exploration ability and is easy to suffer from the local optimal solutions, so it performs poorly on multimodal objective functions. Besides, its unfair balance of exploration and exploitation is another notable shortcoming. To ameliorate these shortcomings and enha

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Khajehzadeh, Mohammad, Amin Iraji, Ali Majdi, Suraparb Keawsawasvong, and Moncef L. Nehdi. "Adaptive Salp Swarm Algorithm for Optimization of Geotechnical Structures." Applied Sciences 12, no. 13 (2022): 6749. http://dx.doi.org/10.3390/app12136749.

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Based on the salp swarm algorithm (SSA), this paper proposes an efficient metaheuristic algorithm for solving global optimization problems and optimizing two commonly encountered geotechnical engineering structures: reinforced concrete cantilever retaining walls and shallow spread foundations. Two new equations for the leader- and followers-position-updating procedures were introduced in the proposed adaptive salp swarm optimization (ASSA). This change improved the algorithm’s exploration capabilities while preventing it from converging prematurely. Benchmark test functions were used to confir

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Heyan Zhang. "Secure Routing Protocol using Salp-Particle Swarm Optimization Algorithm." Journal of Networking and Communication Systems (JNACS) 3, no. 3 (2020): 1–10. http://dx.doi.org/10.46253/jnacs.v3i3.a1.

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Salgotra, Rohit, Urvinder Singh, Supreet Singh, Gurdeep Singh, and Nitin Mittal. "Self-adaptive salp swarm algorithm for engineering optimization problems." Applied Mathematical Modelling 89 (January 2021): 188–207. http://dx.doi.org/10.1016/j.apm.2020.08.014.

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Gao, Zhiwei, and Bo Wang. "Multi-Strategy-Driven Salp Swarm Algorithm for Global Optimization." Journal of Computer and Communications 11, no. 07 (2023): 88–117. http://dx.doi.org/10.4236/jcc.2023.117007.

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Kanoosh, Huthaifa M., Essam Halim Houssein, and Mazen M. Selim. "Salp Swarm Algorithm for Node Localization in Wireless Sensor Networks." Journal of Computer Networks and Communications 2019 (February 19, 2019): 1–12. http://dx.doi.org/10.1155/2019/1028723.

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Nodes localization in a wireless sensor network (WSN) aims for calculating the coordinates of unknown nodes with the assist of known nodes. The performance of a WSN can be greatly affected by the localization accuracy. In this paper, a node localization scheme is proposed based on a recent bioinspired algorithm called Salp Swarm Algorithm (SSA). The proposed algorithm is compared to well-known optimization algorithms, namely, particle swarm optimization (PSO), Butterfly optimization algorithm (BOA), firefly algorithm (FA), and grey wolf optimizer (GWO) under different WSN deployments. The simu

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Agrawal, Anjali, Seema N. Pandey, Laxmi Srivastava, Pratima Walde, R. K. Saket, and Baseem Khan. "Multiobjective Salp Swarm Algorithm Approach for Transmission Congestion Management." International Transactions on Electrical Energy Systems 2022 (December 7, 2022): 1–17. http://dx.doi.org/10.1155/2022/8256908.

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In the newly emerged electric supply industry, the profit maximizing tendency of market participants has developed the problem of transmission congestion as the most crucial issue. This paper proposes a multiobjective salp swarm algorithm (MOSSA) approach for transmission congestion management (CM), implementing demand side management activities. For this, demand response (DR) and distributed generation (DG) have been employed. For willingly reducing the demand, demand response has been called by providing appropriate financial incentives that supports in releasing the congestion over critical

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Saeed, Nagham Tharwat. "A multi-verse Optimizer Approach Based on a Salp Swarm for Image Feature Selection to Observe Changes in Urban Lands." Technium: Romanian Journal of Applied Sciences and Technology 25 (November 10, 2024): 44–52. http://dx.doi.org/10.47577/technium.v25i.8929.

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Many changes have occurred in most urban areas, and it is usually governed by many geographical and social factors, the result will be either the expansion or contraction of these cities. In this paper, an optimizer method called salp swarm optimization (SSO) is used to build a driving force model for urban lands according to the changes in the driving force mechanism. The principle of (SSO) is extracting the driving force classification rules corresponding to different types of land use change samples by imitating the behavior of salp. The classification rules are constructed in the form of "

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Chen, Dongning, Jianchang Liu, Chengyu Yao, Ziwei Zhang, and Xinwei Du. "Multi-strategy improved salp swarm algorithm and its application in reliability optimization." Mathematical Biosciences and Engineering 19, no. 5 (2022): 5269–92. http://dx.doi.org/10.3934/mbe.2022247.

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<abstract> <p>To improve the convergence speed and solution precision of the standard Salp Swarm Algorithm (SSA), a hybrid Salp Swarm Algorithm based on Dimension-by-dimension Centroid Opposition-based learning strategy, Random factor and Particle Swarm Optimization's social learning strategy (DCORSSA-PSO) is proposed. Firstly, a dimension-by-dimension centroid opposition-based learning strategy is added in the food source update stage of SSA to increase the population diversity and reduce the inter-dimensional interference. Secondly, in the followers' position update equation of S

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Mahmood, Alaa Ibrahim, Omar Ibrahim Alsaif, and Ibrahim Ahmed Saleh. "Routing flying Ad Hoc network using salp swarm algorithm." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 2 (2022): 946–53. https://doi.org/10.11591/ijeecs.v28.i2.pp946-953.

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An Ad-hoc network is collection of mobile nodes without the necessity of existing any centralized access points. In this paper introduce novel protocol that used to improveAdHoc protocol with salp swarm algorithm to routed flying Ad Hoc Network (FANET) by method of simulation. FANET predicated unmanned aerial vehicles (UAV), it designed wireless network has nodes withwith high mobility, actively changing topology and movement in 3D space. The main problem for FANET manner of routing packets among managed nodes. The new protocol based on salp swarm algorithm called “SalpAdHoc” proto

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Saha, Bikram, Provas Kumar Roy, and Barun Mandal. "Economic Load Dispatch Incorporating Wind Power Using Hybrid Biogeography-Based Optimization." International Journal of Applied Metaheuristic Computing 12, no. 3 (2021): 54–80. http://dx.doi.org/10.4018/ijamc.2021070103.

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This article represents salp swarm algorithm (SSA) for the most favourable operating solution of economic load dispatch (ELD). For making the convergence first along with SSA, another optimization algorithm (i.e., BBO [biogeography;based optimization]) is also used. For lowering the operational cost, wind power is employed with thermal units. SSA is inspired by swarming behaviour of salp, which belongs to salpiside family. Salp possess a special kind of swarm while hunting for food and navigating. The recommended algorithm is executed on two systems of SIX units and 40 units. In both of the ca

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Borse, Indrabhan, and Hitendra Patil. "Adaptive Beamforming Model for 5G High Speed Networks using Millimeter Wave Communication in Uplink." Review of Computer Engineering Research 9, no. 4 (2022): 209–21. http://dx.doi.org/10.18488/76.v9i4.3160.

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Future generation cellular communications will require increased data rates and transmission using millimeter waves (MMWs), which are an emerging concept to meet this need. The MMW frequencies offer the potential for orders of magnitude capacity improvements. However, MMW network connections are more susceptible to blocking, and they suffer from rapid quality differential. The major limitation of offering multiconnectivity in MMWs is the necessity of tracking the direction of every link with its suitable timing and power. Beamforming enables wireless communications, even with higher frequency

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Anjum, Zeeshan Memon, Dalila Mat Said, Mohammad Yusri Hassan, Zohaib Hussain Leghari, and Gul Sahar. "Parallel operated hybrid Arithmetic-Salp swarm optimizer for optimal allocation of multiple distributed generation units in distribution networks." PLOS ONE 17, no. 4 (2022): e0264958. http://dx.doi.org/10.1371/journal.pone.0264958.

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The installation of Distributed Generation (DG) units in the Radial Distribution Networks (RDNs) has significant potential to minimize active power losses in distribution networks. However, inaccurate size(s) and location(s) of DG units increase power losses and associated Annual Financial Losses (AFL). A comprehensive review of the literature reveals that existing analytical, metaheuristic and hybrid algorithms employed on DG allocation problems trap in local or global optima resulting in higher power losses. To address these limitations, this article develops a parallel hybrid Arithmetic Opt

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Zhang, Chen, Kourosh Sedghisigarchi, Rachel Sheinberg, Shashank Narayana Gowda, and Rajit Gadh. "Optimizing Voltage Stability in Distribution Networks via Metaheuristic Algorithm-Driven Reactive Power Compensation from MDHD EVs." World Electric Vehicle Journal 14, no. 11 (2023): 310. http://dx.doi.org/10.3390/wevj14110310.

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The deployment of medium-duty and heavy-duty (MDHD) electric vehicles (EVs), characterized by their substantial battery capacity and high charging power demand, poses a potential threat to voltage stability within distribution networks. One possible solution to voltage instability is reactive power compensation from charging MDHD EVs. However, this process must be carefully facilitated in order to be effective. This paper introduces an innovative distribution network voltage stability solution by first identifying the network’s weakest buses and then utilizing a metaheuristic algorithm to sche

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Zhao, Yanchun, Senlin Bi, Huanlong Zhang, and Zhiwu Chen. "Dynamic Weight and Mapping Mutation Operation-Based Salp Swarm Algorithm for Global Optimization." Applied Sciences 13, no. 15 (2023): 8960. http://dx.doi.org/10.3390/app13158960.

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The salp swarm algorithm imitates the swarm behavior of salps during navigation and hunting that has been proven the superiority of search for best solution. However, although it has sufficient global search ability, it is still worth paying attention to problems of falling into local optima and lower convergence accuracy. This paper proposes some improvements to the salp swarm algorithm that are based on a nonlinear dynamic weight and the mapping mutation operation. Firstly, the nonlinear dynamic weight is helpful for further optimizing the transition from exploration to exploitation and alle

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Saafan, Mahmoud M., and Eman M. El-Gendy. "IWOSSA: An improved whale optimization salp swarm algorithm for solving optimization problems." Expert Systems with Applications 176 (August 2021): 114901. http://dx.doi.org/10.1016/j.eswa.2021.114901.

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Gurav, Shashidhar B., Kshama V. Kulhalli, and Veena V. Desai. "PROSTATE CANCER DETECTION USING HISTOPATHOLOGY IMAGES AND CLASSIFICATION USING IMPROVED RideNN." Biomedical Engineering: Applications, Basis and Communications 31, no. 06 (2019): 1950042. http://dx.doi.org/10.4015/s101623721950042x.

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Medical industry reports prostate cancer as common and high among men and alarms the necessity for detecting prostate cancer for which the required morphology is extracted from the histopathology images. Commonly, the Gleason grading system remains a perfect factor for grading prostate cancer in men, but pathologists suffer from minute inter- and intra-observer variations. Thus, an automatic method for segmenting and classifying prostate cancer is modeled in this paper. The significance of the developed method is that the segmentation and classification are gland-oriented using the Color Space

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Bouchekara, Houssem, Mostafa Smail, Mohamed Javaid, and Sami Shamsah. "Optimization Design of Electromagnetic Devices Using an Enhanced Salp Swarm Algorithm." Applied Computational Electromagnetics Society 35, no. 12 (2021): 1471–76. http://dx.doi.org/10.47037/2020.aces.j.351203.

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An Enhanced version of the Salp Swarm Algorithm (SSA) referred to as (ESSA) is proposed in this paper for the optimization design of electromagnetic devices. The ESSA has the same structure as of the SSA with some modifications in order to enhance its performance for the optimization design of EMDs. In the ESSA, the leader salp does not move around the best position with a fraction of the distance between the lower and upper bounds as in the SAA; rather, a modified mechanism is used. The performance of the proposed algorithm is tested on the widely used Loney’s solenoid and TEAM Workshop Probl

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Boursianis, Achilles D., Maria S. Papadopoulou, Marco Salucci, et al. "Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers." Applied Sciences 11, no. 18 (2021): 8330. http://dx.doi.org/10.3390/app11188330.

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Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear a

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Gao, Hongyuan, Yangyang Hou, Shibo Zhang, and Ming Diao. "An Efficient Approximation for Nakagami-mQuantile Function Based on Generalized Opposition-Based Quantum Salp Swarm Algorithm." Mathematical Problems in Engineering 2019 (August 14, 2019): 1–13. http://dx.doi.org/10.1155/2019/8291063.

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With the further research in communication systems, especially in wireless communication systems, a statistical model called Nakagami-mdistribution appears to have better performance than other distributions, including Rice and Rayleigh, in explaining received faded envelopes. Therefore, the Nakagami-mquantile function plays an important role in numerical calculations and theoretical analyses for wireless communication systems. However, it is quite difficult to operate numerical calculations and theoretical analyses because Nakagami-mquantile function has no exact closed-form expression. In or

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Mohammed, Shahad Ibrahim, Nazar K. Hussein, Outman Haddani, Mansourah Aljohani, Mohammed Abdulrazaq Alkahya, and Mohammed Qaraad. "Fine-Tuned Cardiovascular Risk Assessment: Locally Weighted Salp Swarm Algorithm in Global Optimization." Mathematics 12, no. 2 (2024): 243. http://dx.doi.org/10.3390/math12020243.

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The Salp Swarm Algorithm (SSA) is a bio-inspired metaheuristic optimization technique that mimics the collective behavior of Salp chains hunting for food in the ocean. While it demonstrates competitive performance on benchmark problems, the SSA faces challenges with slow convergence and getting trapped in local optima like many population-based algorithms. To address these limitations, this study proposes the locally weighted Salp Swarm Algorithm (LWSSA), which combines two mechanisms into the standard SSA framework. First, a locally weighted approach is introduced and integrated into the SSA

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Pallavi Khare. "Multihop Routing Using Chaotic Salp Swarm Optimization Algorithm in WSN." Journal of Networking and Communication Systems (JNACS) 4, no. 1 (2021): 17–24. http://dx.doi.org/10.46253/jnacs.v4i1.a3.

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Zhao, Xiaoqiang, Fan Yang, Yazhou Han, and Yanpeng Cui. "An Opposition-Based Chaotic Salp Swarm Algorithm for Global Optimization." IEEE Access 8 (2020): 36485–501. http://dx.doi.org/10.1109/access.2020.2976101.

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Alabrah, Amerah. "An Efficient NIDPS with Improved Salp Swarm Feature Optimization Method." Applied Sciences 13, no. 12 (2023): 7002. http://dx.doi.org/10.3390/app13127002.

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Network security problems arise these days due to many challenges in cyberspace. The malicious attacks on installed wide networks are rapidly spreading due to their vulnerability. Therefore, the user and system information are at high risk due to network attacks. To protect networks against these attacks, Network Intrusion Detection and Prevention Systems (NIDPS) are installed on them. These NIDPS can detect malicious attacks by monitoring abnormal behavior and patterns in network traffic. These systems were mainly developed using Artificial Intelligence (AI) algorithms. These intelligent NIDP

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李, 端洋. "An Improved Salp Swarm Algorithm for Con-strained Optimization Problems." Advances in Applied Mathematics 12, no. 05 (2023): 2128–37. http://dx.doi.org/10.12677/aam.2023.125216.

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R., Aishwarya, and Mathivanan G. "Improved salp swarm algorithm based optimization of mobile task offloading." PeerJ Computer Science 11 (May 7, 2025): e2818. https://doi.org/10.7717/peerj-cs.2818.

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Background The realization of computation-intensive applications such as real-time video processing, virtual/augmented reality, and face recognition becomes possible for mobile devices with the latest advances in communication technologies. This application requires complex computation for better user experience and real-time decision-making. However, the Internet of Things (IoT) and mobile devices have computational power and limited energy. Executing these computational-intensive tasks on edge devices may result in high energy consumption or high computation latency. In recent times, mobile

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Ibrahim Mahmood, Alaa, Omar Ibrahim Alsaif, and Ibrahim Ahmed Saleh. "Routing flying Ad Hoc network using salp swarm algorithm." Indonesian Journal of Electrical Engineering and Computer Science 28, no. 2 (2022): 946. http://dx.doi.org/10.11591/ijeecs.v28.i2.pp946-953.

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An Ad-hoc network is collection of mobile nodes without the necessity of existing any centralized access points. In this paper introduce novel protocol that used to improveAdHoc protocol with salp swarm algorithm to routed flying Ad Hoc Network (FANET) by method of simulation. FANET predicated unmanned aerial vehicles (UAV), it designed wireless network has nodes withwith high mobility, actively changing topology and movement in 3D space. The main problem for FANET manner of routing packets among managed nodes. The new protocol based on salp swarm algorithm called “SalpAdHoc” protocol to solve

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Ahmed, Mohammed M. "SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network." Indian Journal of Data Communication and Networking 1, no. 2 (2021): 16–20. http://dx.doi.org/10.35940/ijdcn.b5006.041221.

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In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node locatio

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Ahmed, Mohammed M. "SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network." Indian Journal of Data Communication and Networking 1, no. 2 (2021): 16–20. http://dx.doi.org/10.54105/ijdcn.b5006.041221.

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In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node locatio

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Gürses, Dildar, Sujin Bureerat, Sadiq M. Sait, and Ali Rıza Yıldız. "Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications." Materials Testing 63, no. 5 (2021): 448–52. http://dx.doi.org/10.1515/mt-2020-0076.

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Abstract This paper focuses on a comparision of recent algorithms such as the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm. The slime mold algorithm (SMA) is a recent optimization algorithm. In order to strengthen its exploitation and exploration abilities, in this paper, a new hybrid slime mold algorithm-simulated annealing algorithm (HSMA-SA) has been applied to structural engineering design problems. As a result of the rules and practices that have become mandatory for fuel emissions by international o

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Wisam, Najm Al-Din Abed, Abbood Imran Omar, and Najim Abdullah Ali. "Sensored speed control of brushless DC motor based salp swarm algorithm." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 5 (2022): 4832–40. https://doi.org/10.11591/ijece.v12i5.pp4832-4840.

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This article uses one of the newest and efficient meta-heuristic optimization algorithms inspired from nature called salp swarm algorithm (SSA). It imitates the exploring and foraging behavior of salps in oceans. SSA is proposed for parameters tuning of speed controller in brushless DC (BLDC) motor to achieve the best performance. The suggested work modeling and control scheme is done using MATLAB/Simulink and coding environments. In this work, a 6-step inverter is feeding a BLDC motor with a Hall sensor effect. The proposed technique is compared with other nature-inspired techniques such as c

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Liu, Haipeng, Shaomi Duan, and Huilong Luo. "A hybrid engineering algorithm of the seeker algorithm and particle swarm optimization." Materials Testing 64, no. 7 (2022): 1051–89. http://dx.doi.org/10.1515/mt-2021-2138.

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Abstract A newly hybrid algorithm is proposed based on the combination of seeker optimization algorithm and particle swarm optimization. The hybrid algorithm is based on a double population evolution strategy, and the populations of individuals are evolved from the seeker optimization algorithm and the particle swarm optimization separately. The populations of individuals employ an information sharing mechanism to implement coevolution. The hybrid algorithm enhances the individuals’ diversity and averts fall into the local optimum. The hybrid algorithm is compared with particle swarm optimizat

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Yahya, Randa Jalaa, and Nizar Hadi Abbas. "Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 1 (2022): 293. http://dx.doi.org/10.11591/ijece.v12i1.pp293-302.

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A newly hybrid nature-inspired algorithm called HSSGWOA is presented with the combination of the salp swarm algorithm (SSA) and grey wolf optimizer (GWO). The major idea is to combine the salp swarm algorithm's exploitation ability with the grey wolf optimizer's exploration ability to generate both variants' strength. The proposed algorithm uses to tune the parameters of the integral sliding mode controller (ISMC) that design to improve the dynamic performance of the two-link flexible joint manipulator. The efficiency and the capability of the proposed hybrid algorithm are evaluated based on t

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