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Harris Hawks Optimization Algorithm: Variants and Applications

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Abstract

This paper introduces a comprehensive survey of a new swarm intelligence optimization algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO is counted as an example of the most effective Optimization algorithm and utilized in different problems in various domains, successfully. For example, energy and Power Flow, engineering, medical applications, networks, and image processing. This review introduces the available related works of HHO where the main topics include; HHO variants, modification, and Hybridization, HHO applications, analysis and differentiation between HHO and other algorithms in the literature. Finally, the conclusions concentrate on the existing work on HHO, showing its disadvantages, and propose future works. The review paper will be helpful for the researchers and practitioners of HHO belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. Also, it will aid those who are interested by providing them with potential future research.

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References

  1. Abbasi A, Firouzi B, Sendur P (2019) On the application of harris hawks optimization (hho) algorithm to the design of microchannel heat sinks. Eng Comput 37:1409–1428

  2. Abd Elaziz M, Heidari AA, Fujita H, Moayedi H (2020) A competitive chain-based harris hawks optimizer for global optimization and multi-level image thresholding problems. Appl Soft Comput 95:106347

  3. Abdel-Basset M, Ding W, El-Shahat D (2020) A hybrid harris hawks optimization algorithm with simulated annealing for feature selection. Artif Intell Rev 54(1):593–637

  4. Abdel-Basset M, El-shahat D, Elhoseny M, Song H (2020) Energy-aware metaheuristic algorithm for industrial internet of things task scheduling problems in fog computing applications. IEEE Internet of Things J 8(16):12638–12649

  5. Abdelmadjid C, Mohamed S-A, Boussad B (2013) Cfd analysis of the volute geometry effect on the turbulent air flow through the turbocharger compressor. Energy Procedia 36:746–755

    Article  Google Scholar 

  6. Abualigah L, Shehab M, Alshinwan M, Alabool H, Abuaddous HY, Khasawneh AM, Al Diabat M (2020) Ts-gwo: Iot tasks scheduling in cloud computing using grey wolf optimizer. In: Swarm intelligence for cloud computing. Chapman and Hall/CRC, Boca Raton, pp 127–152

  7. Abualigah L, Almotairi KH, Abd Elaziz M, Shehab M, Altalhi M (2022) Enhanced flow direction arithmetic optimization algorithm for mathematical optimization problems with applications of data clustering. Eng Anal Bound Elem 138:13–29

    Article  MathSciNet  MATH  Google Scholar 

  8. Abualigah L, Almotairi KH, Al-qaness MA, Ewees AA., Yousri D, Abd Elaziz M, Nadimi-Shahraki MH (2022) Efficient text document clustering approach using multi-search arithmetic optimization algorithm. Knowl Based Syst 248:108833

  9. Abualigah L, Diabat A, Svetinovic D, Elaziz MA (2022) Boosted harris hawks gravitational force algorithm for global optimization and industrial engineering problems. J Intell Manuf. https://doi.org/10.1007/s10845-022-01921-4

  10. Abualigah L, Elaziz MA, Sumari P, Khasawneh AM, Alshinwan M, Mirjalili S, Shehab M, Abuaddous HY, Gandomi AH (2022) Black hole algorithm: a comprehensive survey. Appl Intell. https://doi.org/10.1007/s10489-021-02980-5

  11. Agushaka JO, Ezugwu AE, Abualigah L (2022) Dwarf mongoose optimization algorithm. Comput Methods Appl Mech Eng 391:114570

    Article  MathSciNet  MATH  Google Scholar 

  12. Ahmad M, Khaja IA, Baz A, Alhakami H, Alhakami W (2020) Particle swarm optimization based highly nonlinear substitution-boxes generation for security applications. IEEE Access 8:116132–116147

    Article  Google Scholar 

  13. Akdag O, Ates A, Yeroglu C (2020) Modification of harris hawks optimization algorithm with random distribution functions for optimum power flow problem. Neural Comput Appl 33(6):1959–1985

  14. Aleem SHA, Zobaa AF, Balci ME, Ismael SM (2019) Harmonic overloading minimization of frequency-dependent components in harmonics polluted distribution systems using harris hawks optimization algorithm. IEEE Access 7:100824–100837

    Article  Google Scholar 

  15. Almaiah MA, Al-Zahrani A, Almomani O, Alhwaitat AK (2021) Classification of cyber security threats on mobile devices and applications. In: Artificial intelligence and blockchain for future cybersecurity applications. Springer, Cham, pp 107–123

  16. Almomani O (2020) A feature selection model for network intrusion detection system based on PSO, GWO, FFA and GA algorithms. Symmetry 12(6):1046

    Article  Google Scholar 

  17. Almomani O (2021) A hybrid model using bio-inspired metaheuristic algorithms for network intrusion detection system. Comput. Mater. Continua 68(1):409–429

    Article  MathSciNet  Google Scholar 

  18. Almomani SN, Shehab M, Al Ebbini MM, Shami AA (2021) The efficiency and effectiveness of the cyber security in maintaining the cloud accounting information. Acad Strateg Manag J 20:1–11

    Google Scholar 

  19. Alsalibi AI, Shambour MKY, Abu-Hashem MA, Shehab M, Shambour Q, Muqat R, (2022) Nonvolatile memory-based internet of things: a survey. In: Artificial Intelligence-based Internet of Things systems. Springer, Cham, pp 285–304

  20. Alsaryrah O, Mashal I, Chung T-Y (2018) Bi-objective optimization for energy aware internet of things service composition. IEEE Access 6:26809–26819

    Article  Google Scholar 

  21. Alsaryrah O, Mashal I, Chung T-Y (2018) Energy-aware services composition for internet of things. In: 2018 IEEE 4th world forum on Internet of Things (WF-IoT). IEEE, pp 604–608

  22. Alshinwan M, Abualigah L, Shehab M, Elaziz MA, Khasawneh AM, Alabool H, Hamad HA (2021) Dragonfly algorithm: a comprehensive survey of its results, variants, and applications. Multimedia Tools Appl 80(10):14979–15016

    Article  Google Scholar 

  23. Amini S, Homayouni S, Safari A, Darvishsefat AA (2018) Object-based classification of hyperspectral data using random forest algorithm. Geo-spatial Inf Sci 21(2):127–138

    Article  Google Scholar 

  24. Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1–12

    Article  Google Scholar 

  25. Attiya I, Abd Elaziz M, Xiong S (2020) Job scheduling in cloud computing using a modified harris hawks optimization and simulated annealing algorithm. Comput Intell Neurosci 2020:3504642

  26. Bai Q (2010) Analysis of particle swarm optimization algorithm. Comput Inf Sci 3(1):180

    Article  Google Scholar 

  27. Bajpai P, Kumar M (2010) Genetic algorithm-an approach to solve global optimization problems. Indian J Compu Sci Eng 1(3):199–206

    Google Scholar 

  28. Bao X, Jia H, Lang C (2019) A novel hybrid harris hawks optimization for color image multilevel thresholding segmentation. IEEE Access 7:76529–76546

    Article  Google Scholar 

  29. Barshandeh S, Piri F, Sangani SR (2020) HMPA: an innovative hybrid multi-population algorithm based on artificial ecosystem-based and harris hawks optimization algorithms for engineering problems. Eng Comput 38:1581–1625

  30. Bednarz JC (1988) Cooperative hunting harris’ hawks (Parabuteo unicinctus). Science 239(4847):1525–1527

    Article  Google Scholar 

  31. Bhat SJ, Venkata SK (2020) An optimization based localization with area minimization for heterogeneous wireless sensor networks in anisotropic fields. Comput Netw 179:107371

    Article  Google Scholar 

  32. Bui DT, Moayedi H, Kalantar B, Osouli A, Gör M, Pradhan B, Nguyen H, Rashid ASA (2019) Harris hawks optimization: a novel swarm intelligence technique for spatial assessment of landslide susceptibility. Sensors 19(16):3590

    Article  Google Scholar 

  33. Bui DT, Moayedi H, Kalantar B, Osouli A, Pradhan B, Nguyen H, Rashid ASA (2019) A novel swarm intelligence-harris hawks optimization for spatial assessment of landslide susceptibility. Sensors 19(16):3590

    Article  Google Scholar 

  34. ÇetınbaŞ İ, Tamyürek B, Demırtaş M (2022) The hybrid harris hawks optimizer-arithmetic optimization algorithm: A new hybrid algorithm for sizing optimization and design of microgrids. IEEE Access 10:19254–19283

    Article  Google Scholar 

  35. Ceylan H, Ceylan H (2009) Harmony search algorithm for transport energy demand modeling. In: Geem ZW (ed) Music-inspired harmony search algorithm. Springer, Berlin, pp 163–172

  36. Chen H, Heidari AA, Chen H, Wang M, Pan Z, Gandomi AH (2020) Multi-population differential evolution-assisted harris hawks optimization: framework and case studies. Future Gen Comput Syst 111:175–198

  37. Chen H, Jiao S, Wang M, Heidari AA, Zhao X (2020) Parameters identification of photovoltaic cells and modules using diversification-enriched harris hawks optimization with chaotic drifts. J Clean Prod 244:118778

    Article  Google Scholar 

  38. Darwish A (2018) Bio-inspired computing: algorithms review, deep analysis, and the scope of applications. Future Comput Inf J 3(2):231–246

    Article  MathSciNet  Google Scholar 

  39. Debjit K, Islam MS, Rahman MA, Pinki FT, Nath RD, Al-Ahmadi S, Hossain MS, Mumenin KM, Awal MA (2022) An improved machine-learning approach for covid-19 prediction using harris hawks optimization and feature analysis using shap. Diagnostics 12(5):1023

    Article  Google Scholar 

  40. DeBruyne AS, Kaur BD (2016) Harris’s hawk multi-objective optimizer for reference point problems. In: Proceeding of the international conference on artificial intelligence (ICAI). The Steering Committee of the World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), p 287

  41. Devarapalli R, Bhattacharyya B (2019) Application of modified harris hawks optimization in power system oscillations damping controller design. In: 2019 8th international conference on power systems (ICPS). IEEE, pp 1–6

  42. Dhawale D, Kamboj VK (2020) HHHO-IGWO: a new hybrid harris hawks optimizer for solving global optimization problems. In: 2020 international conference on computation, automation and knowledge management (ICCAKM). IEEE, pp 52–57

  43. Dhiman G, Kaur A (2019) Stoa: a bio-inspired based optimization algorithm for industrial engineering problems. Eng Appl Artif Intell 82:148–174

    Article  Google Scholar 

  44. Diaaeldin IM, Aleem SHA, El-Rafei A, Abdelaziz AY, Ćalasan M (2020) Optimal network reconfiguration and distributed generation allocation using harris hawks optimization. In: 2020 24th international conference on information technology (IT). IEEE, pp 1–6

  45. Ding W, Abdel-Basset M, Eldrandaly KA, Abdel-Fatah L, de Albuquerque VHC (2020) Smart supervision of cardiomyopathy based on fuzzy harris hawks optimizer and wearable sensing data optimization: a new model. IEEE Trans Cybern 51(10):4944–4958

  46. Du P, Wang J, Hao Y, Niu T, Yang W (2020) A novel hybrid model based on multi-objective Harris hawks optimization algorithm for daily PM2.5 and PM10 forecasting. Appl Soft Comput 96:106620

  47. Eiben AE, Smit SK (2011) Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm Evol Comput 1(1):19–31

    Article  Google Scholar 

  48. Elkasem AH, Kamel S, Korashy A, Jurado F (2020) Application of harris hawks algorithm for frequency response enhancement of two-area interconnected power system with DIFG based wind turbine. In: IEEE 21st international middle east power systems conference (MEPCON 2019), Cairo, Egypt

  49. Erol OK, Eksin I (2006) A new optimization method: big bang-big crunch. Adv Eng Softw 37(2):106–111

    Article  Google Scholar 

  50. Essa F, Abd Elaziz M, Elsheikh AH (2020) An enhanced productivity prediction model of active solar still using artificial neural network and harris hawks optimizer. Appl Therm Eng 170:115020

    Article  Google Scholar 

  51. Ewees AA, Abd Elaziz M (2020) Performance analysis of chaotic multi-verse harris hawks optimization: a case study on solving engineering problems. Eng Appl Artif Intell 88:103370

    Article  Google Scholar 

  52. Fan C, Zhou Y, Tang Z (2020) Neighborhood centroid opposite-based learning harris hawks optimization for training neural networks. Evol Intell 1–21

  53. Fan Q, Chen Z, Xia Z (2020) A novel quasi-reflected harris hawks optimization algorithm for global optimization problems. Soft Comput 19(3):1–19

  54. Formato RA (2007) Central force optimization. Prog Electromagn Res 77:425–491

    Article  Google Scholar 

  55. Fu W, Shao K, Tan J, Wang K (2020) Fault diagnosis for rolling bearings based on composite multiscale fine-sorted dispersion entropy and svm with hybrid mutation sca-hho algorithm optimization. IEEE Access 8:13086–13104

    Article  Google Scholar 

  56. Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76(2):60–68

  57. Gezici H, Livatyalı H (2022) Chaotic harris hawks optimization algorithm. J Comput Des Eng 9(1):216–245

    Article  Google Scholar 

  58. Glover F (1977) Heuristics for integer programming using surrogate constraints. Decis Sci 8(1):156–166

    Article  Google Scholar 

  59. Golilarz NA, Gao H, Demirel H (2019) Satellite image de-noising with harris hawks meta heuristic optimization algorithm and improved adaptive generalized Gaussian distribution threshold function. IEEE Access 7:57459–57468

    Article  Google Scholar 

  60. Golilarz NA, Mirmozaffari M, Gashteroodkhani TA, Ali L, Dolatsara HA, Boskabadi A, Yazdi M (2020) Optimized wavelet-based satellite image de-noising with multi-population differential evolution-assisted harris hawks optimization algorithm. IEEE Access 8:133076–133085

    Article  Google Scholar 

  61. Guo L, Wang G-G, Wang H, Wang D (2013) An effective hybrid firefly algorithm with harmony search for global numerical optimization. Sci World J 13:30–44

    Google Scholar 

  62. Gupta S, Deep K, Heidari AA, Moayedi H, Wang M (2020) Opposition-based learning harris hawks optimization with advanced transition rules: principles and analysis. Expert Syst Appl 158:113510

  63. Ha, EA, Kamel S, Korashy A, Jurado F (2019) Application of harris hawks algorithm for frequency response enhancement of two-area interconnected power system with DFIG based wind turbine. In: 2019 21st international middle east power systems conference (MEPCON). IEEE, pp 568–574

  64. Heidari M (2016) Improving efficiency of photovoltaic system by using neural network mppt and predictive control of converter. Int J Renew Energy Res 6(4):1524–1529

    Google Scholar 

  65. Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Future Gen Comput Syst 97:849–872

    Article  Google Scholar 

  66. Holland J (1975) Adaptation in natural and artificial systems: an introductory analysis with application to biology. Control Artif Intell 3:1–15

    Google Scholar 

  67. Houssein EH, Hosney ME, Elhoseny M, Oliva D, Mohamed WM, Hassaballah M (2020) Hybrid harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics. Sci Rep 10(1):1–22

    Article  Google Scholar 

  68. Houssein EH, Hosney ME, Oliva D, Mohamed WM, Hassaballah M (2020) A novel hybrid harris hawks optimization and support vector machines for drug design and discovery. Comput Chem Eng 133:106656

    Article  Google Scholar 

  69. Houssein EH, Saad MR, Hussain K, Zhu W, Shaban H, Hassaballah M (2020) Optimal sink node placement in large scale wireless sensor networks based on Harris’ hawk optimization algorithm. IEEE Access 8:19381–19397

    Article  Google Scholar 

  70. Hu H, Ao Y, Bai Y, Cheng R, Xu T (2020) An improved harris’ hawks optimization for sar target recognition and stock market index prediction. IEEE Access 8:65891–65910

    Article  Google Scholar 

  71. Hu J, Heidari AA, Shou Y, Ye H, Wang L, Huang X, Chen H, Chen Y, Wu P et al (2022) Detection of covid-19 severity using blood gas analysis parameters and Harris hawks optimized extreme learning machine. Comput Biol Med 142:105166

    Article  Google Scholar 

  72. Hussain K, Zhu W, Salleh MNM (2019) Long-term memory Harris’ hawk optimization for high dimensional and optimal power flow problems. IEEE Access 7:147596–147616

    Article  Google Scholar 

  73. Hussien AG, Amin M (2022) A self-adaptive harris hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection. Int J Mach Learn Cybern 13(2):309–336

    Article  Google Scholar 

  74. Islam MZ, Wahab NIA, Veerasamy V, Hizam H, Mailah NF, Khan A, Sabo A (2019) Optimal power flow using a novel Harris hawk optimization algorithm to minimize fuel cost and power loss. In: 2019 IEEE conference on sustainable utilization and development in engineering and technologies (CSUDET). IEEE, pp 246–250

  75. Jia H, Lang C, Oliva D, Song W, Peng X (2019) Dynamic harris hawks optimization with mutation mechanism for satellite image segmentation. Remote Sensing 11(12):1421

    Article  Google Scholar 

  76. Jia H, Peng X, Kang L, Li Y, Jiang Z, Sun K (2020) Pulse coupled neural network based on harris hawks optimization algorithm for image segmentation. Multimedia Tools Appl 79(37):28369–28392

    Article  Google Scholar 

  77. Jiao S, Chong G, Huang C, Hu H, Wang M, Heidari AA, Chen H, Zhao X (2020) Orthogonally adapted Harris hawk optimization for parameter estimation of photovoltaic models. Energy 203:117804

  78. Jouhari H, Lei D, Al-qaness MA, Elaziz MA, Damaševičius R, Korytkowski M, Ewees AA (2020) Modified harris hawks optimizer for solving machine scheduling problems. Symmetry 12(9):1460

    Article  Google Scholar 

  79. Kamboj VK, Nandi A, Bhadoria A, Sehgal S (2020) An intensify harris hawks optimizer for numerical and engineering optimization problems. Applied Soft Computing 89:106018

    Article  Google Scholar 

  80. Kennedy J (2010) Particle swarm optimization. In: Sammut C, Webb GI (eds) Encyclopedia of machine learning, vol 12. Springer, Boston, pp 760–766

  81. Khalifeh S, Akbarifard S, Khalifeh V, Zallaghi E (2020) Optimization of water distribution of network systems using the Harris hawks optimization algorithm (case study: Homashahr city). MethodsX 7:100948

  82. Khan A, Sulaiman M, Alhakami H, Alhindi A (2020) Analysis of oscillatory behavior of heart by using a novel neuroevolutionary approach. IEEE Access 8:86674–86695

    Article  Google Scholar 

  83. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680

    Google Scholar 

  84. Koza JR (1994) Genetic programming II: automatic discovery of reusable programs. MIT, Cambridge

  85. Koziel S, Yang X-S (2011) Computational optimization, methods and algorithms, vol 356. Springer, Heidelberg

  86. Kulturel-Konak S, Smith AE, Coit DW (2003) Efficiently solving the redundancy allocation problem using tabu search. IIE Trans 35(6):515–526

    Article  Google Scholar 

  87. Kumar M, Kulkarni AJ, Satapathy SC (2018) Socio evolution & learning optimization algorithm: a socio-inspired optimization methodology. Future Gen Comput Syst 81:252–272

    Article  Google Scholar 

  88. Kurtuluş E, Yıldız AR, Sait SM, Bureerat S (2020) A novel hybrid Harris hawks-simulated annealing algorithm and rbf-based metamodel for design optimization of highway guardrails. Mater Test 62(3):251–260

    Article  Google Scholar 

  89. Li C, Li J, Chen H (2020) A meta-heuristic-based approach for qos-aware service composition. IEEE Access 8:69579–69592

    Article  Google Scholar 

  90. Liu Y, Wang G, Chen H, Dong H, Zhu X, Wang S (2011) An improved particle swarm optimization for feature selection. J Bionic Eng 8(2):191–200

    Article  Google Scholar 

  91. Mansoor M, Mirza AF, Ling Q (2020) Harris hawk optimization-based mppt control for pv systems under partial shading conditions. J Clean Prod 274:122857

    Article  Google Scholar 

  92. Milad A (2013) Harmony search algorithm: strengths and weaknesses. J Comput Eng Inf Technol 2(1):1–7

    Google Scholar 

  93. Mirjalili S (2015) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl Based Syst 89:228–249

    Article  Google Scholar 

  94. Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67

    Article  Google Scholar 

  95. Moayedi H, Osouli A, Nguyen H, Rashid ASA (2019) A novel Harris hawks’ optimization and k-fold cross-validation predicting slope stability. Eng Comput 9:1–11

  96. Moayedi H, Gör M, Lyu Z, Bui DT (2020) Herding behaviors of grasshopper and harris hawk for hybridizing the neural network in predicting the soil compression coefficient. Measurement 152:107389

    Article  Google Scholar 

  97. Murata T, Ishibuchi H, Tanaka H (1996) Multi-objective genetic algorithm and its applications to flowshop scheduling. Comput Ind Eng 30(4):957–968

    Article  Google Scholar 

  98. Nalcaci G, Yildirim D, Ermis M (2020) Selective harmonic elimination for light-rail transportation motor drives using harris hawks algorithm. In: 2020 IEEE International conference on environment and electrical engineering and 2020 IEEE industrial and commercial power systems Europe (EEEIC/I &CPS Europe). IEEE, pp 1–6

  99. Ouaarab A, Ahiod B, Yang X-S (2014) Discrete cuckoo search algorithm for the travelling salesman problem. Neural Comput Appl 24(7–8):1659–1669

    Article  Google Scholar 

  100. Oyelade ON, Ezugwu AE-S, Mohamed TI, Abualigah L (2022) Ebola optimization search algorithm: a new nature-inspired metaheuristic optimization algorithm. IEEE Access 10:16150–16177

    Article  Google Scholar 

  101. Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1(1):33–57

    Article  Google Scholar 

  102. Qu C, He W, Peng X, Peng X (2020) Harris hawks optimization with information exchange. Appl Math Model 84:52–75

  103. Rajendran S, Khalaf OI, Alotaibi Y, Alghamdi S (2021) Mapreduce-based big data classification model using feature subset selection and hyperparameter tuned deep belief network. Sci Rep 11(1):1–10

    Article  Google Scholar 

  104. Ramachandran M, Mirjalili S, Nazari-Heris M, Parvathysankar DS, Sundaram A, Gnanakkan CARC (2022) A hybrid grasshopper optimization algorithm and harris hawks optimizer for combined heat and power economic dispatch problem. Eng Appl Artif Intell 111:104753

    Article  Google Scholar 

  105. Rammurthy D, Mahesh P (2020) Whale harris hawks optimization based deep learning classifier for brain tumor detection using mri images. J King Saud Univ Comput Inf Sci 34(6):3259–3272

  106. Rao RV, Savsani VJ, Vakharia D (2012) Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf Sci 183(1):1–15

    Article  MathSciNet  Google Scholar 

  107. Rashedi E, Nezamabadi-Pour H, Saryazdi S (2009) Gsa: a gravitational search algorithm. Inf Sci 179(13):2232–2248

    Article  MATH  Google Scholar 

  108. Ridha HM, Heidari AA, Wang M, Chen H (2020) Boosted mutation-based harris hawks optimizer for parameters identification of single-diode solar cell models. Energy Convers Manag 209:112660

    Article  Google Scholar 

  109. Rodríguez-Esparza E, Zanella-Calzada LA, Oliva D, Heidari AA, Zaldivar D, Pérez-Cisneros M, Foong LK (2020) An efficient harris hawks-inspired image segmentation method. Expert Syst Appl 155(2):113428

  110. Sahoo BP, Panda S (2020) Load frequency control of solar photovoltaic/wind/biogas/biodiesel generator based isolated microgrid using harris hawks optimization. In: 2020 First international conference on power, control and computing technologies (ICPC2T). IEEE, pp 188–193

  111. Salgotra R, Singh U, Saha S (2018) New cuckoo search algorithms with enhanced exploration and exploitation properties. Expert Syst Appl 95:384–420

    Article  Google Scholar 

  112. Sammen SS, Ghorbani MA, Malik A, Tikhamarine Y, AmirRahmani M, Al-Ansari N, Chau K-W (2020) Enhanced artificial neural network with harris hawks optimization for predicting scour depth downstream of ski-jump spillway. Appl Sci 10(15):5160

    Article  Google Scholar 

  113. Saravanan G, Ibrahim AM, Kumar DS, Vanitha U, Chandrika V (2020) Iot based speed control of BLDC motor with harris hawks optimization controller. Int J Grid Distrib Comput 13(1):1902–1915

    Google Scholar 

  114. Schmitt BI (2015) Convergence analysis for particle swarm optimization. FAU University Press, Erlangen

  115. Selim A, Kamel S, Alghamdi AS, Jurado F (2020) Optimal placement of dgs in distribution system using an improved harris hawks optimizer based on single-and multi-objective approaches. IEEE Access 8:52815–52829

    Article  Google Scholar 

  116. Seyfollahi A, Ghaffari A (2020) Reliable data dissemination for the Internet of Things using harris hawks optimization. Peer-to-Peer Netw Appl 13(3):1–17

  117. Shambour MKY, Khan EA (2022) A late acceptance hyper-heuristic approach for the optimization problem of distributing pilgrims over mina tents. JUCS J Univers Comput Sci 28(4):396–413. https://doi.org/10.3897/jucs.72900

    Article  Google Scholar 

  118. Shambour MKY, Abusnaina AA, Alsalibi AI (2019) Modified global flower pollination algorithm and its application for optimization problems. Interdiscip Sci Comput Life Sci 11(3):496–507

    Google Scholar 

  119. Shehab M, Khader AT (2020) Modified cuckoo search algorithm using a new selection scheme for unconstrained optimization problems. Curr Med Imaging 16(4):307–315

    Article  Google Scholar 

  120. Shehab M, Khader AT, Al-Betar MA (2017) A survey on applications and variants of the cuckoo search algorithm. Appl Soft Comput 61:1041–1059

    Article  Google Scholar 

  121. Shehab M, Khader AT, Al-Betar MA, Abualigah LM (2017) Hybridizing cuckoo search algorithm with hill climbing for numerical optimization problems. In: 2017 8th International conference on information technology (ICIT). IEEE, pp 36–43

  122. Shehab M, Khader AT, Laouchedi M, Alomari OA (2018) Hybridizing cuckoo search algorithm with bat algorithm for global numerical optimization. J Supercomput 75(5):2395–2422

  123. Shehab M, Khader A, Laouchedi M (2018) A hybrid method based on cuckoo search algorithm for global optimization problems. J Inf Commun Technol 17(3):469–491

    Article  Google Scholar 

  124. Shehab M, Khader AT, Alia MA (2019) Enhancing cuckoo search algorithm by using reinforcement learning for constrained engineering optimization problems. In: 2019 IEEE Jordan international joint conference on electrical engineering and information technology (JEEIT). IEEE, pp 812–816

  125. Shehab M, Abualigah L, Al Hamad H, Alabool H, Alshinwan M, Khasawneh AM (2020) Moth-flame optimization algorithm: variants and applications. Neural Comput Appl 32(14):9859–9884

    Article  Google Scholar 

  126. Shehab M, Alshawabkah H, Abualigah L, AL-Madi N (2021) Enhanced a hybrid moth-flame optimization algorithm using new selection schemes. Eng Comput 37(4):2931–2956

  127. Shehabeldeen TA, Abd Elaziz M, Elsheikh AH, Zhou J (2019) Modeling of friction stir welding process using adaptive neuro-fuzzy inference system integrated with harris hawks optimizer. J Mater Res Technol 8(6):5882–5892

    Article  Google Scholar 

  128. Sihwail R, Omar K, Ariffin KAZ, Tubishat M (2020) Improved harris hawks optimization using elite opposition-based learning and novel search mechanism for feature selection. IEEE Access 8:121127–121145

    Article  Google Scholar 

  129. Singh N, Houssein EH, Singh SB, Dhiman G (2022) HSSAHHO: a novel hybrid Salp swarm-Harris hawks optimization algorithm for complex engineering problems. J Ambient Intell Humaniz Comput 1–37

  130. Sobhy M, Ezzat M, Hasanien HM, Abdelaziz AY (2019) Harris hawks algorithm for automatic generation control of interconnected power systems. In: 2019 21st international middle east power systems conference (MEPCON). IEEE, pp 575–582

  131. Sol D, Duncan RP, Blackburn TM, Cassey P, Lefebvre L (2005) Big brains, enhanced cognition, and response of birds to novel environments. Proc Natl Acad Sci USA 102(15):5460–5465

    Article  Google Scholar 

  132. Song M, Jia H, Abualigah L, Liu Q, Lin Z, Wu D, Altalhi M (2022) Modified harris hawks optimization algorithm with exploration factor and random walk strategy. Comput Intell Neurosci 2022:4673665

  133. Srinivas M, Amgoth T (2020) Ee-hhhss: Energy-efficient wireless sensor network with mobile sink strategy using hybrid harris hawk-salp swarm optimization algorithm. Int J Commun Syst 33(16):e4569

  134. Storn R, Price K (1997) Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341–359

    Article  MathSciNet  MATH  Google Scholar 

  135. Thaher T, Arman N (2020) Efficient multi-swarm binary Harris hawks optimization as a feature selection approach for software fault prediction. In: 2020 11th International conference on information and communication dystems (ICICS). IEEE, pp 249–254

  136. Tikhamarine Y, Souag-Gamane D, Ahmed AN, Sammen SS, Kisi O, Huang YF, El-Shafie A (2020) Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization. J Hydrol 589:125133

  137. Too J, Abdullah AR, Mohd Saad N (2019) A new quadratic binary harris hawk optimization for feature selection. Electronics 8(10):1130

    Article  Google Scholar 

  138. Wang L, Yang R, Xu Y, Niu Q, Pardalos PM, Fei M (2013) An improved adaptive binary harmony search algorithm. Inf Sci 232:58–87

    Article  MathSciNet  Google Scholar 

  139. Waseem W, Sulaiman M, Alhindi A, Alhakami H (2020) A soft computing approach based on fractional order DPSO algorithm designed to solve the corneal model for eye surgery. IEEE Access 8:61576–61592

    Article  Google Scholar 

  140. Wei Y, Lv H, Chen M, Wang M, Heidari AA, Chen H, Li C (2020) Predicting entrepreneurial intention of students: an extreme learning machine with Gaussian Barebone Harris hawks optimizer. IEEE Access 8:76841–76855

    Article  Google Scholar 

  141. Wright AH (1991) Genetic algorithms for real parameter optimization. In: Foundations of genetic algorithms, vol. 1. Elsevier, Amsterdam, pp 205–218

  142. Wróblewski J (1996) Theoretical foundations of order-based genetic algorithms. Fundam Inf 28(3–4):423–430

    Article  MathSciNet  MATH  Google Scholar 

  143. Wunnava A, Naik MK, Panda R, Jena B, Abraham A (2020) An adaptive Harris hawks optimization technique for two dimensional grey gradient based multilevel image thresholding. Appl Soft Comput 95:106526

    Article  Google Scholar 

  144. Wunnava A, Naik MK, Panda R, Jena B, Abraham A (2020) A differential evolutionary adaptive Harris hawks optimization for two dimensional practical masi entropy-based multilevel image thresholding. J King Saud Univ Comput Inf Sci 34(6):3011–3024

  145. Xie W, Xing C, Wang J, Guo S, Guo M-W, Zhu L-F (2020) Hybrid Henry gas solubility optimization algorithm based on the harris hawk optimization. IEEE Access 8:144665–144692

    Article  Google Scholar 

  146. Yang X-S (2009) Firefly algorithms for multimodal optimization. In: Watanabe O, Zeugmann T (eds) Stochastic algorithms: foundations and applications. Springer, Berlin, pp 169–178

  147. Yang X-S, Deb S (2009) Cuckoo search via lévy flights. In: 2009 World congress on nature & biologically inspired computing (NaBIC). IEEE, pp 210–214

  148. Yang X-S, Deb S (2014) Cuckoo search: recent advances and applications. Neural Comput Appl 24(1):169–174

    Article  Google Scholar 

  149. Yıldız AR, Yıldız BS, Sait SM, Bureerat S, Pholdee N (2019) A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems. Mater Test 61(8):735–743

    Article  Google Scholar 

  150. Yousri D, Allam D, Eteiba MB (2020) Optimal photovoltaic array reconfiguration for alleviating the partial shading influence based on a modified Harris hawks optimizer. Energy Convers Manag 206:112470

    Article  Google Scholar 

  151. Yousri D, Babu TS, Fathy A (2020) Recent methodology based Harris hawks optimizer for designing load frequency control incorporated in multi-interconnected renewable energy plants. Sustain Energy Grids Netw 22:100352

    Google Scholar 

  152. Yu J, Kim C-H, Rhee S-B (2020) The comparison of lately proposed Harris hawks optimization and Jaya optimization in solving directional overcurrent relays coordination problem. Complexity 2020:3807653

  153. Yu Z, Shi X, Zhou J, Chen X, Qiu X (2020) Effective assessment of blast-induced ground vibration using an optimized random forest model based on a Harris hawks optimization algorithm. Appl Sci 10(4):1403

    Article  Google Scholar 

  154. Zhang J, Sanderson AC (2009) JADE: adaptive differential evolution with optional external archive. IEEE Trans Evol Comput 13(5):945–958

    Article  Google Scholar 

  155. Zhang H, Sun G (2002) Feature selection using tabu search method. Pattern Recogn 35(3):701–711

    Article  MATH  Google Scholar 

  156. Zhang J, Zhou Y, Luo Q (2018) An improved sine cosine water wave optimization algorithm for global optimization. J Intell Fuzzy Syst 34(4):2129–2141

    Article  Google Scholar 

  157. Zhang X, Zhao K, Niu Y (2020) Improved harris hawks optimization based on adaptive cooperative foraging and dispersed foraging strategies. IEEE Access 8:160297–160314

    Article  Google Scholar 

  158. Zhang Y, Liu R, Wang X, Chen H, Li C (2020) Boosted binary harris hawks optimizer and feature selection. Structure 25:26

  159. Zhang Y, Zhou X, Shih PC (2020) Modified Harris Hawks optimization algorithm for global optimization problems. Arab J Sci Eng 45(12):10949–10974

  160. Zhao L, Li Z, Chen H, Li J, Xiao J, Yousefi N (2020) A multi-criteria optimization for a CCHP with the fuel cell as primary mover using modified harris hawks optimization. Recov Util Environ Effects Energy Sources Part A. https://doi.org/10.1080/15567036.2020.1784320

  161. Zheng-Ming G, Juan Z, Yu-Rong H, Chen H-F (2019) The improved harris hawk optimization algorithm with the tent map. In: 2019 3rd International conference on electronic information technology and computer engineering (EITCE). IEEE, pp 336–339

  162. Zingg DW, Nemec M, Pulliam TH (2008) A comparative evaluation of genetic and gradient-based algorithms applied to aerodynamic optimization. Eur J Comput Mech 17(1–2):103–126

    MATH  Google Scholar 

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Acknowledgements

The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4361183DSR03).

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Shehab, M., Mashal, I., Momani, Z. et al. Harris Hawks Optimization Algorithm: Variants and Applications. Arch Computat Methods Eng 29, 5579–5603 (2022). https://doi.org/10.1007/s11831-022-09780-1

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