- Jayabarathi, T., Sadasivam, G., and Ramachandran, V., “Evolutionary programming based multi-area economic dispatch with tie line constraints”, Electric Machines & Power Systems, Vol. 28, No. 12, (2000), 1165-1176. doi: 10.1080/073135600449044.
- Manoharan, P.S., Kannan, P.S., Baskar, S., and Iruthayarajan, M., “Evolutionary algorithm solution and KKT based optimality verification to multi-area economic dispatch”, International Journal of Electrical Power & Energy Systems, Vol. 31, No. 7-8, (2009), 365-73. doi: 10.1016/j.ijepes.2009.03.010.
- Sharma, M., Manjaree, P., and Laxmi. S., “Reserve constrained multi-area economic dispatch employing differential evolution with timevarying mutation”, International journal of Electrical Power & Energy Systems, Vol. 33, No. 3, (2011), 753-66. doi: 10.1016/j.ijepes.2010.12.033.
- Somasundaram P., and Jothi Swaroopan, N.M., “Fuzzified Particle Swarm Optimization Algorithm for Multi-area Security Constrained Economic Dispatch”, Electric Power Components and Systems, Vol. 39, No. 10, (2011), 979-990. doi: 10.1080/15325008.2011.552094.
- Basu, M., “Artificial bee colony optimization for multi-area economic dispatch,” International journal of Electrical Power & Energy Systems, Vol. 49, (2013), 181-187. doi:10.1016/j.ijepes.2013.01.004.
- Basu, M., “Teaching–learning-based optimization algorithm for multi-area economic dispatch”, Energy, Vol. 68, (2014), 21-28. doi: 10.1016/j.energy.2014.02.064.
- Basu, M., “Fast Convergence Evolutionary Programming for Multi-area Economic Dispatch”, Electric Power Components and Systems, Vol. 45, No. 15, (2017), 1629-1637. doi: 10.1080/15325008.2017.1376234.
- Nguyen, K.P., Dinh, N.D., and Fujita, G., “Multi-area economic dispatch using hybrid cuckoo search algorithm”, In: 50th International Universities Power Engineering Conference (UPEC), Stoke on Trent, UK; (2015), 1-6. doi:10.1109/UPEC.2015.7339777.
- Ghasemi, M., Aghaei, J., Akbari, E., Ghavidel, S., and Li, L., “A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems,” Energy, Vol. 107, (2016), 182–195. doi: 10.1016/j.energy.2016.04.002.
- Zhang, P., Ma, W., and Dong, Y., “Multi-area economic dispatching using improved grasshopper optimization algorithm”, Evolving Systems, (2019). doi: 10.1007/s12530-019-09320-6.
- Valinejad, J., Oladi, Z., Barforoushi, T., and Parvania, M., “Stochastic unit commitment in the presence of demand response program under uncertainties”, International Journal of Engineering, Transactions B: Applications, Vol. 30, No. 8, (2017), 1134-1143. doi: 10.5829/ije.2017.30.08b.04.
- Razzaghi, T., and Kianfar, F., “The optimal energy carriers’ substitutes in thermal power plants: A fuzzy linear programming model”, International Journal of Engineering, Transactions C: Aspects, Vol. 25, No. 1, (2012), 55-66. doi:10.5829/idosi.ije.2012.25.01c.07.
- Bagheri, A., Sadafi, M., and Safikhani, H., “Multi-objective optimization of solar thermal energy storage using hybrid of particle swarm optimization, multiple crossover and mutation operator”, International Journal of Engineering, Transactions B: Applications, Vol. 24, No. 3, (2011), 367-376. doi:10.5829/idosi.ije.2011.24.04b.07.
- Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M., and Tavakkoli-Moghaddam, R., “Red deer algorithm (RDA): a new nature-inspired meta-heuristic,” Soft Computing, Vol. 24, (2020), 14637-14665. doi: 10.1007/s00500-020-04812-z.
Fathollahi-Fard, A.M., Azari, M.N., and Hajiaghaei-Keshteli, M., “An improved red deer algorithm to address a direct current brushless motor design problem,” Scientia Iranica, (2019). doi: 10.24200/SCI.2019.51909.2419.