[1] Duan, D.-L., Ling, X.-D., Wu, X.-Y., & Zhong, B. (2015). Reconfiguration of distribution network for loss reduction and reliability improvement based on an enhanced genetic algorithm. International Journal of Electrical Power & Energy Systems, 64, 88-95. https://doi.org/10.1016/j.ijepes.2014.07.036
[2] Amini, S., Ghasemi, S., & Moshtagh, J. (2021). Distribution feeder reconfiguration using PSOGSA algorithm in presence of distribution generation based on a fuzzy approach. Computational Intelligence in Electrical Engineering, 12(3), 73-86.
[3] Kansal, S., Kumar, V., & Tyagi, B. (2013). Optimal placement of different type of DG sources in distribution networks. International Journal of Electrical Power & Energy Systems, 53, 752-760. https://doi.org/10.1016/j.ijepes.2013.05.040
[4] Nguyen, T. T., Nguyen, T. T., Truong, V. A., Nguyen, Q. T., & Phung, T. A. (2017). Multi-objective electric distribution network reconfiguration solution using runner-root algorithm. Applied Soft Computing, 52, 93-108. https://doi.org/10.1016/j.asoc.2016.12.018
[5] Kanwar, N., Gupta, N., Niazi, K. R., & Swarnkar, A. (2016). An integrated approach for distributed resource allocation and network reconfiguration considering load diversity among customers. Sustainable Energy, Grids and Networks, 7, 37-46. https://doi.org/10.1016/j.segan.2016.05.002
[6] Wang, H.-J., Pan, J.-S., Nguyen, T.-T., & Weng, S. (2022). Distribution network reconfiguration with distributed generation based on parallel slime mould algorithm. Energy, 244, 123011. https://doi.org/10.1016/j.energy.2021.123011
[7] Fathi, R., Tousi, B., & Galvani, S. (2023). Allocation of renewable resources with radial distribution network reconfiguration using improved salp swarm algorithm. Applied Soft Computing, 132, 109828. https://doi.org/10.1016/j.asoc.2022.109828
[8] Niknam, T., Kavousifard, A., & Aghaei, J. (2012). Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation. IET Renewable Power Generation, 6(4), 236-247. https://doi.org/10.1049/iet-rpg.2011.0256
[9] Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: Harmony search. Simulation, 76(2), 60-68. https://doi.org/10.1177/003754970107600201
[10] Geem, Z. W., Tseng, C.-L., & Park, Y. (2005). Harmony search for generalized orienteering problem: Best touring in China. In L. Wang, K. Chen, & Y. S. Ong (Eds.), Advances in Natural Computation (LNCS vol. 3612, pp. 741-750). Springer. https://doi.org/10.1007/11539902_91
[11] Siahbalaee, J., Rezanejad, N., & Gharehpetian, G. B. (2019). Reconfiguration and DG sizing and placement using improved shuffled frog leaping algorithm. Electric Power Components and Systems, 47(16-17), 1475-1488. https://doi.org/10.1080/15325008.2019.1689449
[12] Lotfi, H., Azizivahed, A., Shojaei, A. A., Seyedi, S., & Othman, M. F. B. (2021). Multi-objective distribution feeder reconfiguration along with optimal sizing of capacitors and distributed generators regarding network voltage security. Electric Power Components and Systems, 49(6-7), 652-668. https://doi.org/10.1080/15325008.2021.2011486
[13] Ghosh, S., & Sherpa, K. S. (2008). An efficient method for load-flow solution of radial distribution networks. International Journal of Electrical Power & Energy Systems Engineering, 1(2), 108-115.
[14] Prakash, K., & Sydulu, M. (2007). Particle swarm optimization based capacitor placement on radial distribution systems. In 2007 IEEE Power Engineering Society General Meeting (pp. 1-5). IEEE. https://doi.org/10.1109/PES.2007.386149
[15] Baran, M. E., & Wu, F. F. (1989). Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Transactions on Power Delivery, 4(2), 1401-1407. https://doi.org/10.1109/61.25627
[16] Srinivasa Rao, R., Narasimham, S. V. L., Ramalinga Raju, M., & Srinivasa Rao, A. (2011). Optimal network reconfiguration of large-scale distribution system using harmony search algorithm. IEEE Transactions on Power Systems, 26(3), 1080-1088. https://doi.org/10.1109/TPWRS.2010.2076839