Dec/19/2017 GA Variants: 1. Run /rBGA/run_rBGA.m to solve the economic dispatch by rBGA for IEEE 6-unit system. Change the parameters of the system in SystemModel.m. 2. Run /rFNGA/run_rFNGA.m to solve the economic dispatch by rFNGA for IEEE 6-unit system. Change the parameters of the system in SystemModel.m. 3. Run /rKGA/run_rKGA.m to solve the economic dispatch by rKGA for IEEE 6-unit system. Change the parameters of the system in SystemModel.m. 4. Run /rTRGA/run_rTRGA.m to solve the economic dispatch by rTRGA for IEEE 6-unit system. Change the parameters of the system in SystemModel.m. 5. Run /rUGA/run_rUGA.m to solve the economic dispatch by rUGA for IEEE 6-unit system. Change the parameters of the system in SystemModel.m. Please use the following references: (1) For KGA, FNGA - use: Md Tamjidul Hoque*, Sumaiya Iqbal, “Genetic Algorithm based Improved Sampling for Protein Structure Prediction,” International Journal of Bio-Inspired Computation, International Journal of Bio-Inspired Computation, Volume 9, Issue 3, 2017 pp. 129 – 141. (2) For TRGA - use:Md Tamjidul Hoque*, M. Chetty, Andrew Lewis, Abdul Sattar, “Twin Removal in Genetic Algorithms for Protein Structure Prediction using Low Resolution Model.” IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), Jan-Mar: 2011, Vol 8, no. 1, pp.234-245. Otherwise, use: Samin Rastgoufard, Sumaiya Iqbal, Md Tamjidul Hoque, Dimitrios Charalampidis, "Genetic Algorithm Variant based Effective Solutions for Economic Dispatch Problems", Accepted in TPEC 2018 (The 2018 IEEE Texas Power and Energy Conference), USA. Contact PI: Md Tamjidul Hoque, email: thoque@uno.edu or, tamjidul.hoque@gmail.com. --- x ---