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58. Wei, J.; Chen, Y.; Yu, Y.; Chen, Y. Optimal randomness in swarm-based search. *Mathematics* **2019**, *7*, 828. [CrossRef]

59. Kahraman, H.T.; Aras, S.; Gedikli, E. Fitness-distance balance (FDB): A new selection method for meta-heuristic search algorithms. *Knowl. Based Syst.* **2020**, *190*, 105169. [CrossRef]

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62. Xu, Y.; Peng, Y.; Su, X.; Yang, Z.; Ding, C.; Yang, X. Improving teaching–learning-based-optimization algorithm by a distance-fitness learning strategy. *Knowl. Based Syst.* **2022**, *257*, 108271. [CrossRef]

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64. Basu, M. Quasi-oppositional differential evolution for optimal reactive power dispatch. *Int. J. Electr. Power Energy Syst.* **2016**, *78*, 29–40. [CrossRef]

65. Warid, W.; Hizam, H.; Mariun, N.; Wahab, N.I.A. A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution. *Appl. Soft Comput.* **2018**, *65*, 360–373. [CrossRef]

66. Guha, D.; Roy, P.; Banerjee, S. Quasi-oppositional symbiotic organism search algorithm applied to load frequency control. *Swarm Evol. Comput.* **2017**, *33*, 46–67. [CrossRef]

67. Dutta, S.; Paul, S.; Roy, P.K. Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem. *J. Electr. Syst. Inf. Technol.* **2018**, *5*, 83–98. [CrossRef]

68. Guha, D.; Roy, P.K.; Banerjee, S. Quasi-oppositional differential search algorithm applied to load frequency control. *Eng. Sci. Technol. Int. J.* **2016**, *19*, 1635–1654. [CrossRef]

69. Shehadeh, H.A. Chernobyl disaster optimizer (CDO): A novel meta-heuristic method for global optimization. *Neural Comput.* **2023**, *35*, 10733–10749. [CrossRef]
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74. Seyyedabbasi, A.; Kiani, F. Sand Cat swarm optimization: A nature-inspired algorithm to solve global optimization problems. *Eng. Comput.* **2022**, *39*, 2627–2651. [CrossRef]

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78. Mohapatra, S.; Mohapatra, P. American zebra optimization algorithm for global optimization problems. *Sci. Rep.* **2023**, *13*, 5211. [CrossRef] [PubMed]

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80. Ehsan, A.; Yang, Q. Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques. *Appl. Energy* **2018**, *210*, 44–59. [CrossRef]

81. Augustine, N.; Suresh, S.; Moghe, P.; Sheikh, K. Economic dispatch for a microgrid considering renewable energy cost functions. In *Proceedings of the 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington, DC, USA*, 16–20 January 2012; IEEE: Piscataway, NJ, USA; pp. 1–7.

82. Gampa, S.R.; Das, D. Optimum placement and sizing of DGs considering average hourly variations of load. *Int. J. Electr. Power Energy Syst.* **2015**, *66*, 25–40. [CrossRef]

83. Sultana, S.; Roy, P.K. Optimal capacitor placement in radial distribution systems using teaching learning based optimization. *Int. J. Electr. Power Energy Syst.* **2014**, *54*, 387–398. [CrossRef]

84. El-Fergany, A. Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. *Int. J. Electr. Power Energy Syst.* **2015**, *64*, 1197–1205. [CrossRef]

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
70. Zhao, W.; Wang, L.; Mirjalili, S. Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications. *Comput. Methods Appl. Mech. Eng.* **2022**, *388*, 114194. [CrossRef]

71. Zhao, S.; Zhang, T.; Ma, S.; Chen, M. Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications. *Eng. Appl. Artif. Intell.* **2022**, *114*, 105075. [CrossRef]

72. Geem, Z.W.; Kim, J.H.; Loganathan, G.V. A new heuristic optimization algorithm: Harmony search. *Simulation* **2001**, *76*, 60–68. [CrossRef]

73. Wang, L.; Cao, Q.; Zhang, Z.; Mirjalili, S.; Zhao, W. Artificial rabbits optimization: A new bio-inspired meta-heuristic algorithm for solving engineering optimization problems. *Eng. Appl. Artif. Intell.* **2022**, *114*, 105082. [CrossRef]

74. Seyyedabbasi, A.; Kiani, F. Sand Cat swarm optimization: A nature-inspired algorithm to solve global optimization problems. *Eng. Comput.* **2022**, *39*, 2627–2651. [CrossRef]

75. Faramarzi, A.; Heidarinejad, M.; Stephens, B.; Mirjalili, S. Equilibrium optimizer: A novel optimization algorithm. *Knowl. Based Syst.* **2020**, *191*, 105190. [CrossRef]

76. Jamil, M.; Yang, X.-S. A literature survey of benchmark functions for global optimisation problems. *Int. J. Math. Model. Numer. Optim.* **2013**, *4*, 150–194. [CrossRef]

77. Molga, M.; Smutnicki, C. Test functions for optimization needs. *Test Funct. Optim. Needs* **2005**, *101*, 48.

78. Mohapatra, S.; Mohapatra, P. American zebra optimization algorithm for global optimization problems. *Sci. Rep.* **2023**, *13*, 5211. [CrossRef] [PubMed]

79. Zhang, D.; Fu, Z.; Zhang, L. An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems. *Electr. Power Syst. Res.* **2007**, *77*, 685–694. [CrossRef]

80. Ehsan, A.; Yang, Q. Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques. *Appl. Energy* **2018**, *210*, 44–59. [CrossRef]

81. Augustine, N.; Suresh, S.; Moghe, P.; Sheikh, K. Economic dispatch for a microgrid considering renewable energy cost functions. In *Proceedings of the 2012 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington, DC, USA*, 16–20 January 2012; IEEE: Piscataway, NJ, USA; pp. 1–7.

82. Gampa, S.R.; Das, D. Optimum placement and sizing of DGs considering average hourly variations of load. *Int. J. Electr. Power Energy Syst.* **2015**, *66*, 25–40. [CrossRef]

83. Sultana, S.; Roy, P.K. Optimal capacitor placement in radial distribution systems using teaching learning based optimization. *Int. J. Electr. Power Energy Syst.* **2014**, *54*, 387–398. [CrossRef]

84. El-Fergany, A. Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. *Int. J. Electr. Power Energy Syst.* **2015**, *64*, 1197–1205. [CrossRef]

**Disclaimer/Publisher's Note:** The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.