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Journal articles on the topic 'WOA-BAT'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Mohammed, Hardi M., Shahla U. Umar, and Tarik A. Rashid. "A Systematic and Meta-Analysis Survey of Whale Optimization Algorithm." Computational Intelligence and Neuroscience 2019 (April 28, 2019): 1–25. http://dx.doi.org/10.1155/2019/8718571.

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The whale optimization algorithm (WOA) is a nature-inspired metaheuristic optimization algorithm, which was proposed by Mirjalili and Lewis in 2016. This algorithm has shown its ability to solve many problems. Comprehensive surveys have been conducted about some other nature-inspired algorithms, such as ABC and PSO. Nonetheless, no survey search work has been conducted on WOA. Therefore, in this paper, a systematic and meta-analysis survey of WOA is conducted to help researchers to use it in different areas or hybridize it with other common algorithms. Thus, WOA is presented in depth in terms

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Hidayat, Nur Wahyu, Purwanto, and Fikri Budiman. "Whale Optimization Algorithm Bat Chaotic Map Multi Frekuensi for Finding Optimum Value." Journal of Applied Intelligent System 5, no. 2 (2021): 80–90. http://dx.doi.org/10.33633/jais.v5i2.4432.

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Optimization is one of the most interesting things in life. Metaheuristic is a method of optimization that tries to balance randomization and local search. Whale Optimization Algorithm (WOA) is a metaheuristic method that is inspired by the hunting behavior of humpback whales. WOA is very competitive compared to other metaheuristic algorithms, but WOA is easily trapped in a local optimum due to the use of encircling mechanism in its search space resulting in low performance. In this research, the WOA algorithm is combined with the BAT chaotic map multi-frequency (BCM) algorithm. This method is

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Dutta, Sayantan, and Ayan Banerjee. "Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm." December 2020 2, no. 4 (2020): 195–208. http://dx.doi.org/10.36548/jscp.2020.4.001.

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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) an

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Kanagaraj, Ganesan, SAR Sheik Masthan, and Vincent F. Yu. "Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits." MENDEL 28, no. 1 (2022): 41–54. http://dx.doi.org/10.13164/mendel.2022.1.041.

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In robot-assisted manufacturing or assembly, following a predefined path became a critical aspect. In general, inverse kinematics offers the solution to control the movement of manipulator while following the trajectory. The main problem with the inverse kinematics approach is that inverse kinematics are computationally complex. For a redundant manipulator, this complexity is further increased. Instead of employing inverse kinematics, the complexity can be reduced by using a heuristic algorithm. Therefore, a heuristic-based approach can be used to solve the inverse kinematics of the robot mani

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Saoud, Afaf, and Abdelmadjid Recioui. "Hybrid algorithm for cloud-fog system based load balancing in smart grids." Bulletin of Electrical Engineering and Informatics 11, no. 1 (2022): 477–87. http://dx.doi.org/10.11591/eei.v11i1.3450.

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Energy management is among the key components of smart metering. Its role is to balance energy consumption and distribution. Smart devices integration results in a huge data exchange between different parts of the smart grid causing a delay in the response and processing time. To overcome this latency issue, the cloud computing has been proposed. However, cloud computing does not perform well when there are large distances from the cloud to the consumers. Fog computing solves this issue. In this paper, a cloud-fog computing system is presented to achieve an accurate load balancing. The hybridi

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Afaf, Saoud, and Recioui Abdelmadjid. "Hybrid algorithm for cloud-fog system based load balancing in smart grids." Bulletin of Electrical Engineering and Informatics 11, no. 1 (2022): 477–87. https://doi.org/10.11591/eei.v11i1.3450.

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Energy management is among the key components of smart metering. Its role is to balance energy consumption and distribution. Smart devices integration results in a huge data exchange between different parts of the smart grid causing a delay in the response and processing time. To overcome this latency issue, the cloud computing has been proposed. However, cloud computing does not perform well when there are large distances from the cloud to the consumers. Fog computing solves this issue. In this paper, a cloud-fog computing system is presented to achieve an accurate load balancing. The hybridi

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Flayyih, Kadhim Hayyawi, and Mohsen Nickray. "Energy-efficient clustering in wireless sensor networks using metaheuristic algorithms." Edelweiss Applied Science and Technology 8, no. 6 (2024): 8582–610. https://doi.org/10.55214/25768484.v8i6.3848.

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Energy management in Wireless Sensor Networks (WSNs) remains a critical challenge, particularly in clustering processes. This article compares three optimization algorithms—Grasshopper Optimization Algorithm (GOA), Bat Algorithm (BA), and Whale Optimization Algorithm (WOA)—to achieve energy-efficient clustering and extend network lifetime. Initial cluster head placement is performed using K-means clustering, and a novel cost function is introduced that considers energy consumption and node distribution, enhancing the network’s efficiency and resilience. The algorithms are evaluated across thre

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Sungheetha, Akey, and Rajesh Sharma R. "Fuzzy Chaos Whale Optimization and BAT Integrated Algorithm for Parameter Estimation in Sewage Treatment." March 2021 3, no. 1 (2021): 10–18. http://dx.doi.org/10.36548/jscp.2021.1.002.

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Biological and social issues rise with faults that occur in waste water treatment plant (WWTP). Nature as well as humans are negatively impacted by the dangerous effects of poorly treated wastewater. This paper combines the fuzzy logic, chaos theory, whale optimization algorithm (WOA) and BAT algorithm (FCW-BAT) to create a novel model for parameter estimation. The WWTP applications are exposed to FCW-BAT algorithm for identifying non-well-structured domain, validating decision rules, cost reduction and estimation of several relevant attributes from the complete dataset. The significant data i

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Mohammed, Hardi M., Zrar Kh Abdul, Tarik A. Rashid, Abeer Alsadoon, and Nebojsa Bacanin. "A new K-means grey wolf algorithm for engineering problems." World Journal of Engineering 18, no. 4 (2021): 630–38. http://dx.doi.org/10.1108/wje-10-2020-0527.

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Purpose This paper aims at studying meta-heuristic algorithms. One of the common meta-heuristic optimization algorithms is called grey wolf optimization (GWO). The key aim is to enhance the limitations of the wolves’ searching process of attacking gray wolves. Design/methodology/approach The development of meta-heuristic algorithms has increased by researchers to use them extensively in the field of business, science and engineering. In this paper, the K-means clustering algorithm is used to enhance the performance of the original GWO; the new algorithm is called K-means clustering gray wolf o

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Et.al, Rozlini Mohamed. "An Optimized DiscretizationApproach using k-Means Bat Algorithm." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 1842–51. http://dx.doi.org/10.17762/turcomat.v12i3.1013.

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This study has proposed arelatively new discretization approach using k-means and Bat algorithm in preparation phase of classification problem. In essence, bat algorithm is applied to find the best search space solution. Eventually, the best search space solution is utilized to produce cluster centroid. The cluster centroid is very useful to determine appropriate breakpoint for discretization. The proposed discretization approach is applied in the experiments with continuous datasets. Decision Tree, k-Nearest Neighbours and Naïve Bayes classifiers are used in the experiments. The proposed disc

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Melin, Patricia, Daniela Sánchez, Martha Pulido, and Oscar Castillo. "Comparative Study of Metaheuristic Optimization of Convolutional Neural Networks Applied to Face Mask Classification." Mathematical and Computational Applications 28, no. 6 (2023): 107. http://dx.doi.org/10.3390/mca28060107.

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The preventive measures taken to curb the spread of COVID-19 have emphasized the importance of wearing face masks to prevent potential infection with serious diseases during daily activities or for medical professionals working in hospitals. Due to the mandatory use of face masks, various methods employing artificial intelligence and deep learning have emerged to detect whether individuals are wearing masks. In this paper, we utilized convolutional neural networks (CNNs) to classify the use of face masks into three categories: no mask, incorrect mask, and proper mask. Establishing the appropri

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Punyakum, Voravee, Kanchana Sethanan, Krisanarach Nitisiri, and Rapeepan Pitakaso. "Hybrid Particle Swarm and Whale Optimization Algorithm for Multi-Visit and Multi-Period Dynamic Workforce Scheduling and Routing Problems." Mathematics 10, no. 19 (2022): 3663. http://dx.doi.org/10.3390/math10193663.

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This paper focuses on the dynamic workforce scheduling and routing problem for the maintenance work of harvesters in a sugarcane harvesting operation. Technician teams categorized as mechanical, hydraulic, and electrical teams are assumed to have different skills at different levels to perform services. The jobs are skill-constrained and have time windows. During a working day, a repair request from a sugarcane harvester may arrive, and as time passes, the harvester’s position may shift to other sugarcane fields. We formulated this problem as a multi-visit and multi-period dynamic workforce sc

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Mohamed, Rozlini, and Noor Azah Samsudin. "An improve unsupervised discretization using optimization algorithms for classification problems." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 1344. http://dx.doi.org/10.11591/ijeecs.v34.i2.pp1344-1352.

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This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offerin

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Mohamed, Rozlini, and Noor Azah Samsudin. "An improve unsupervised discretization using optimization algorithms for classification problems." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 1344–52. https://doi.org/10.11591/ijeecs.v34.i2.pp1344-1352.

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This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. The primary objective is to determine the optimal technique for predicting relevant class labels. The paper emphasizes the significance of discretization in data preprocessing, offerin

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Deepak, Malini, and Rabee Rustum. "Review of Latest Advances in Nature-Inspired Algorithms for Optimization of Activated Sludge Processes." Processes 11, no. 1 (2022): 77. http://dx.doi.org/10.3390/pr11010077.

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The activated sludge process (ASP) is the most widely used biological wastewater treatment system. Advances in research have led to the adoption of Artificial Intelligence (AI), in particular, Nature-Inspired Algorithm (NIA) techniques such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) to optimize treatment systems. This has aided in reducing the complexity and computational time of ASP modelling. This paper covers the latest NIAs used in ASP and discusses the advantages and limitations of each algorithm compared to more traditional algorithms that have been utilized over t

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Mathavavisakan, N. Micheal, K. Indhira, and Aliakbar Montazer Haghighi. "Swarm based Heuristic Optimization of the Recurrent Customers and Standby Server Under General Retrial Times." International Journal of Mathematical, Engineering and Management Sciences 10, no. 4 (2025): 931–64. https://doi.org/10.33889/ijmems.2025.10.4.045.

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As queueing theory and modeling deal with queue length, waiting time and busy period, that all affect costs for an in institution and/or a busing corporation, the optimization plays a crucial role in such models. This paper focuses on the performance modeling and optimal configuration of a single-server retrial queue with recurrent customers and a standby server, operating under Bernoulli working vacation conditions. The primary aim of the paper is to analyze the dynamics of this queueing model to achieve minimal operational costs while ensuring high performance. Using the supplementary variab

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Kishore, Bhamidipati, Ali Yasar, Yavuz Selim Taspinar, et al. "Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction." Computational Intelligence and Neuroscience 2022 (August 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/2062944.

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Corn has great importance in terms of production in the field of agriculture and animal feed. Obtaining pure corn seeds in corn production is quite significant for seed quality. For this reason, the distinction of corn seeds that have numerous varieties plays an essential role in marketing. This study was conducted with 14,469 images of BT6470, Calipso, Es_Armandi, and Hiva types of corn licensed by BIOTEK. The classification of images was carried out in three stages. At the first stage, deep feature extraction of the four types of corn images was performed with the pretrained CNN model Squeez

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Goyal, Shanky, Shashi Bhushan, Yogesh Kumar, et al. "An Optimized Framework for Energy-Resource Allocation in a Cloud Environment based on the Whale Optimization Algorithm." Sensors 21, no. 5 (2021): 1583. http://dx.doi.org/10.3390/s21051583.

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Cloud computing offers the services to access, manipulate and configure data online over the web. The cloud term refers to an internet network which is remotely available and accessible at anytime from anywhere. Cloud computing is undoubtedly an innovation as the investment in the real and physical infrastructure is much greater than the cloud technology investment. The present work addresses the issue of power consumption done by cloud infrastructure. As there is a need for algorithms and techniques that can reduce energy consumption and schedule resource for the effectiveness of servers. Loa

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Ivanov, Neagu, Grigoras, and Gavrilas. "Optimal Capacitor Bank Allocation in Electricity Distribution Networks Using Metaheuristic Algorithms." Energies 12, no. 22 (2019): 4239. http://dx.doi.org/10.3390/en12224239.

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Energy losses and bus voltage levels are key parameters in the operation of electricity distribution networks (EDN), in traditional operating conditions or in modern microgrids with renewable and distributed generation sources. Smart grids are set to bring hardware and software tools to improve the operation of electrical networks, using state-of the art demand management at home or system level and advanced network reconfiguration tools. However, for economic reasons, many network operators will still have to resort to low-cost management solutions, such as bus reactive power compensation usi

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Venkatasubramanian, S., A. Suhasini, and C. Vennila. "Cluster Head Selection and Optimal Multipath detection using Coral Reef Optimization in MANET Environment." International Journal of Computer Network and Information Security 14, no. 3 (2022): 88–99. http://dx.doi.org/10.5815/ijcnis.2022.03.07.

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Mobile Ad-hoc Network (MANET) data transfer between nodes in a multi-hop way offers a wide variety of applications. The dynamic feature of ad hoc network mobile nodes is primarily influenced by safety issues, which limit data forwarding rate in multipath routing. As a supplementary method to improve safe data delivery in a MANET, this paper propose and analyse the cluster head (CH) selection and optimum multipath scheme. The CHs are chosen based on the possibility values of each node in MANET, which are considered from the residual energy of each node. During the present phase, the total remai

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Mavuri, Sri Suresh, and Jayaram Nakka. "Economic scheduling and dispatching of distributed generators considering uncertainties in modified 33-bus and modified 69-bus system under different microgrid regions." Transactions on Energy Systems and Engineering Applications 5, no. 2 (2024): 1–22. http://dx.doi.org/10.32397/tesea.vol5.n2.570.

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This paper presents a comprehensive framework for the economic scheduling and dispatching of Distributed Generators (DGs) in modified 33-bus and 69-bus systems across multi-microgrid regions. The framework introduces two key techniques: a novel dispatch strategy for optimizing the charging and discharging of Electric Vehicle (EV) batteries, and a robust power dispatch method for islanded distribution systems. The EV dispatch strategy uses a multi-criteria decision analysis method, Probabilistic Elimination and Choice Expressing Reality (p-ELECTRE), to maximize profits for EV owners while meeti

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Wang, Chia-Hung, Shumeng Chen, Qigen Zhao, and Yifan Suo. "An Efficient End-to-End Obstacle Avoidance Path Planning Algorithm for Intelligent Vehicles Based on Improved Whale Optimization Algorithm." Mathematics 11, no. 8 (2023): 1800. http://dx.doi.org/10.3390/math11081800.

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End-to-end obstacle avoidance path planning for intelligent vehicles has been a widely studied topic. To resolve the typical issues of the solving algorithms, which are weak global optimization ability, ease in falling into local optimization and slow convergence speed, an efficient optimization method is proposed in this paper, based on the whale optimization algorithm. We present an adaptive adjustment mechanism which can dynamically modify search behavior during the iteration process of the whale optimization algorithm. Meanwhile, in order to coordinate the global optimum and local optimum

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Ahmed Shaban, Awaz, and Ibrahim Mahmood Ibrahim. "Swarm intelligence algorithms: a survey of modifications and applications." International Journal of Scientific World 11, no. 1 (2025): 59–65. https://doi.org/10.14419/vhckcq86.

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Swarm Intelligence (SI) is a dynamic subfield of artificial intelligence that draws inspiration from the collective behaviors of natural systems ‎such as ant colonies, bird flocks, and fish schools. This paper provides a comprehensive review of SI algorithms, examining their foundational ‎principles, recent modifications, and applications across diverse domains. Prominent algorithms such as Particle Swarm Optimization (PSO), ‎Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), and Bat Algorithm (BA) are analyzed alongside emerging approaches like Grey ‎Wolf Optimizer (GWO), Zebra Optim

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Abdulsaheb, Jaafar Ahmed, and Dheyaa Jasim Kadhim. "Classical and Heuristic Approaches for Mobile Robot Path Planning: A Survey." Robotics 12, no. 4 (2023): 93. http://dx.doi.org/10.3390/robotics12040093.

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The most important research area in robotics is navigation algorithms. Robot path planning (RPP) is the process of choosing the best route for a mobile robot to take before it moves. Finding an ideal or nearly ideal path is referred to as “path planning optimization.” Finding the best solution values that satisfy a single or a number of objectives, such as the shortest, smoothest, and safest path, is the goal. The objective of this study is to present an overview of navigation strategies for mobile robots that utilize three classical approaches, namely: the roadmap approach (RM), cell decompos

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Kumar Kavuturu, K. V., K. N. V. Sai Tejaswi, and Varaprasad Janamala. "Performance and security enhancement using generalized optimal unified power flow controller under contingency conditions and renewable energy penetrations." Journal of Electrical Systems and Information Technology 9, no. 1 (2022). http://dx.doi.org/10.1186/s43067-022-00057-y.

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AbstractIn this paper, a novel flexible AC transmission system (FACTS) device named generalized optimal unified power flow controller (GOUPFC) is introduced to control the power flows in multi transmission lines and to regulate the voltages and angles at the load buses. The detailed power injection modeling of GOUPFC is presented in this paper. The optimal location of GOUPFC is determined based on line collapse proximity indicator (LCPI). A multi-objective function is framed in terms of average voltage deviation (AVDI), real power loss (Ploss) and average line collapse proximity indicator (LCP

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Bayona, Eduardo, J. Enrique Sierra‐García, and Matilde Santos Peñas. "Improving Safety and Efficiency of Industrial Vehicles by Bio‐Inspired Algorithms." Expert Systems 42, no. 3 (2025). https://doi.org/10.1111/exsy.13836.

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ABSTRACTIn the context of industrial automation, optimising automated guided vehicle (AGV) trajectories is crucial for enhancing operational efficiency and safety. They must travel in crowded work areas and cross narrow corridors with strict safety and time requirements. Bio‐inspired optimization algorithms have emerged as a promising approach to deal with complex optimization scenarios. Thus, this paper explores the ability of three novel bio‐inspired algorithms: the Bat Algorithm (BA), the Whale Optimization Algorithm (WOA) and the Gazelle Optimization Algorithm (GOA); to optimise the AGV pa

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Sharma, Seema, and Narendra Singh Yadav. "A Review on Attack Detection Using Machine Learning with Nature-inspired Optimization Techniques." Recent Patents on Engineering 19 (March 26, 2025). https://doi.org/10.2174/0118722121368672250303051704.

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The security of web applications is a significant issue because of their widespread use in everyday activities. Although machine learning has shown success in identifying attacks, it can face difficulties when dealing with wide datasets. Algorithms inspired by nature, renowned for their optimization capabilities, offer potential solutions to this difficulty. This paper analyses the use of Nature-Inspired Optimization Algorithms (NIOAs) to identify web application threats and assess their performance in detecting web application attackers. This paper involves a comprehensive review of several k

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Abdulrazzaq, Dina Riadh, Narjis Mezaal Shati, and Haider K. Hoomod. "Task Scheduling in a Cloud Environment Based on Meta-Heuristic Approaches: A Survey." Iraqi Journal of Science, February 29, 2024, 1001–23. http://dx.doi.org/10.24996/ijs.2024.65.2.33.

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Cloud computing is one of the emerging technologies that expands the boundaries of the internet by using centralized servers to maintain data and resources. It allows users and consumers to use various applications provided by the cloud provider, but one of the major issues is task scheduling. Task scheduling is employed for the purpose of mapping the requests of users to the appropriate resources available. This paper provides a detailed survey of the available scheduling techniques for cloud environments based on six common metaheuristic algorithms. Those algorithms are the Cuckoo Search Alg

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Ayana, Omer Ayana, Deniz Furkan Kanbak, and Mumine Kaya Keles. "BSO: Binary Sailfish Optimization for feature selection in sentiment analysis." An International Journal of Optimization and Control: Theories & Applications (IJOCTA), January 23, 2025, 1655. https://doi.org/10.36922/ijocta.1655.

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Sentiment analysis (SA) plays a critical role in various domains, providing valuable insights into public opinion regarding brands, products, and events. By leveraging this method, companies can enhance customer satisfaction through informed adjustments to their products. This study aims to implement sentiment analysis on user comments from online sales platforms. We propose and evaluate four machine learning (ML) algorithms alongside a deep learning (DL) model. Moreover, our dataset contains noise data that is unsuitable for classification, which negatively impacts performance. To address thi

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Sahay, Shuvam, Ramanaiah Upputuri, Pooja Kumari, and Niranjan Kumar. "An enhanced arithmetic optimization algorithm for optimal control of reactive power." Optimal Control Applications and Methods, October 3, 2023. http://dx.doi.org/10.1002/oca.3061.

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AbstractIn this article, an enhanced arithmetic optimization algorithm (EAOA) is utilized to resolve the optimal reactive power dispatch problem (ORPD) of power plants, which is a non‐linear, non‐smooth, complex optimization problem. Typically, it is formulated as a constrained optimal power flow problem. This paper utilizes the gamma distribution to generate initial random solutions, which improves the accuracy of the arithmetic optimization algorithm (AOA). The original mode of deviation of math optimizer accelerated (MOA) is replaced with the improved pattern of change in the prey's energy

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Mohammed, Athraa Jasim, and Khalil Ibrahim Ghathwan. "Intelligent Bio-Inspired Whale Optimization Algorithm for Color Image based Segmentation." Pertanika Journal of Science and Technology 28, no. 4 (2020). http://dx.doi.org/10.47836/pjst.28.4.14.

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Color image segmentation is widely used methods for searching of homogeneous regions to classify them into various groups. Clustering is one technique that is used for this purpose. Clustering algorithms have drawbacks such as the finding of optimum centers within a cluster and the trapping in local optima. Even though inspired meta-heuristic algorithms have been adopted to enhance the clustering performance, some algorithms still need improvements. Whale optimization algorithm (WOA) is recognized to be enough competition with common meta-heuristic algorithms, where it has an ability to obtain

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Zhao, Xiaoyan, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, liangyu Li, and Xuwei Guo. "A review of optimization techniques for cost estimation in software development." Intelligent Data Analysis: An International Journal, May 29, 2025. https://doi.org/10.1177/1088467x251330476.

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In software development, cost estimation remains a significant challenge. Despite numerous research efforts, identifying an optimal technique applicable to all situations has proven difficult. The increasing adoption of agile development methods has further complicated accurate cost estimation. Recently, the application of optimization techniques, particularly metaheuristic optimization algorithms, has increased to enhance estimation accuracy and performance. However, there is a lack of systematic literature reviews exploring these optimization techniques in software cost estimation (SCE). Thi

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Devisasi Kala, D. D., and D. Thiripura Sundari. "A review on optimization of antenna array by evolutionary optimization techniques." International Journal of Intelligent Unmanned Systems, December 14, 2021. http://dx.doi.org/10.1108/ijius-08-2021-0093.

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Purpose Optimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques. Design/methodology/approach Design of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due t

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