60. Gampa S.R., and Das D. (2015) Optimum placement and sizing of DGs considering average hourly variation of loads. Int. J. Electr. Power Energy Syst. 66:25-40.
61. Jamil M., and Anees A.S. (2016) Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical benefits. Energy 103:231-239.
62. Garcia J.A.M., and Mena A.J.G. (2013) Optimal distributed generation location and sizing using a modified teaching-learning based optimization algorithm. Int. J. Electr. Power Energy Syst. 50: 65-75.
63. Sultana U., Khairuddin A.B., Mokhtar A.S., Zareen N., and Sultana B. (2016) Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system. Energy 111:525-536.
64. Devi S., and Geethanjali M. (2014) Application of modified bacterial foraging optimization algorithm for optimal placement and sizing of distributed generation. Expert Syst. Appl. 41(6):2772-2781.
65. Das B., Mukherjee V., and Das D. (2016) DG placement in radial distribution network by symbiotic organisms search algorithm for real power loss minimization. Appl. Soft Comput. 49:920-936.
66. Das B., Mukherjee V., and Das D. (2020) Student psychology based optimization algorithm: A new population based optimization algorithm for solving optimization problems. Adv. Engg. Soft. 146: 102804.
67. Sugantham P.N, Hansen N., Liang J.J., Deb K., Chen Y.P., Auger A., Tiwari S. (2005) Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization. Nanyang Technol. Univ., Singapore, Tech. Rep. KanGAL #2005005, IIT Kanpur, India.
68. Barik S., Das D., and Bansal R. C. (2020) DG investment and allocation in active distribution networks, in Uncertainties in Modern Power Systems, Editor-Ahmed F. Zobaa, Shady H.E. Abdel Aleem, Academic Press, Elsevier, pp. 343-394.
69. Clerc, Maurice (2010) Particle swarm optimization. John Wiley & Sons 93.
70. Rao, R. Venkata (2016) Teaching-learning-based optimization algorithm. In Teaching learning based optimization algorithm, Springer, Cham, pp. 9-39.
71. Liao, Tianjun, Daniel Molina, Marco A. Montes de Oca, and Thomas Stützle (2014) A note on bound constraints handling for the IEEE CEC’05 benchmark function suite. Evolutionary computation 22(2): 351-359.
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