Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm

Sayah, 2008, Modified differential evolution algorithm for optimal power flow with non-smooth cost functions, Energy Convers. Manag., 49, 3036, 10.1016/j.enconman.2008.06.014 Ongsakul, 2006, Optimal power flow by improved evolutionary programming, Electr. Power Components Syst., 34, 79, 10.1080/15325000691001458 Subbaraj, 2009, Optimal reactive power dispatch using self adaptive real coded genetic algorithm, Int. J. Electr. Power Syst. Res., 79, 374, 10.1016/j.epsr.2008.07.008 Mahadevan, 2010, Comprehensive learning particle swarm optimization for reactive power dispatch, Appl. Soft Comput., 10, 641, 10.1016/j.asoc.2009.08.038 Varadarajan, 2008, Differential evolution approach for optimal reactive power dispatch, Appl. Soft Comput., 8, 1549, 10.1016/j.asoc.2007.12.002 Hansen, 2006, CMA evolution strategy: a comparing review, Stud. Fuzziness Soft Comput., 192, 75, 10.1007/3-540-32494-1_4 Khazali, 2011, Optimal reactive power dispatch based on harmonic search algorithm, Electr. Power Energy Syst., 33, 684, 10.1016/j.ijepes.2010.11.018 Ertas, 2013, Optimization of fiber reinforced laminates for a maximum fatigue life by using the particle swarm optimization: part-1, Mech. Compos. Mater., 48, 1011, 10.1007/s11029-013-9314-x Cosentino, 2011, 15 Kennedy, 1995, 1942 Favuzza, 2006, Adaptive and dynamic ant colony search algorithm for optimal distribution systems reinforcement strategy, Appl. Intell., 24, 31, 10.1007/s10489-006-6927-y Di Silvestre, 2014, A generalized Framework for optimal sizing of distributed energy Resources in micro-grids using an Indicator-based swarm approach, IEEE Trans. Industrial Informatics, 10, 152, 10.1109/TII.2013.2272945 Yang, 2007, A modified particle swarm optimizer with dynamic adaption, Appl. Math. Comput., 189, 1205, 10.1016/j.amc.2006.12.045 Basu, 2014, Improved differential evolution for economic dispatch, Electr. Power Energy Syst., 63, 855, 10.1016/j.ijepes.2014.07.003 NareshBabu, 2014, Analysis of optimal power flow problem based on two stage initialization algorithm, Electr. Power Energy Syst., 55, 91, 10.1016/j.ijepes.2013.08.011 Mandal, 2014, Economic load dispatch using krill herd algorithm, Electr. Power Energy Syst., 57, 1, 10.1016/j.ijepes.2013.11.016 Bouchekara, 2014, Optimal power flow using teaching-learning-based optimization technique, 114, 49 Bhattacharjee, 2014, Solution of economic load dispatch problems of power systems by real coded Chemical Reaction algorithm, Electr. Power Energy Syst., 59, 176, 10.1016/j.ijepes.2014.02.006 Santos Coelho, 2014, Differential evolution based on truncated Levy-type flights and population diversity measure to solve economic load dispatch problems, Electr. Power Energy Syst., 57, 178, 10.1016/j.ijepes.2013.11.024 Li, 2014, Energy saving dispatch with complex constraints: prohibited zones, valve point effect and carbon tax, Electr. Power Energy Syst., 63, 657, 10.1016/j.ijepes.2014.06.013 Niu, 2014, A hybrid search with arithmetic crossover operation for economic dispatch, Electr. Power Energy Syst., 62, 237, 10.1016/j.ijepes.2014.04.031 Hosseinnezhad, 2014, Species-based Quantum Particle Swarm Optimization for economic load dispatch, Electr. Power Energy Syst., 63, 311, 10.1016/j.ijepes.2014.05.066 Bhattacharjee, 2014, Oppositional real coded chemical Re- action optimization for different economic dispatch problems, Electr. Power Energy Syst., 55, 378, 10.1016/j.ijepes.2013.09.033 Christry, 2014, Adaptive biogeography based predator-prey optimization technique for optimal power flow, Electr. Power Energy Syst., 62, 344, 10.1016/j.ijepes.2014.04.054 Lu, 2014, Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effects, Electr. Power Energy Syst., 62, 130, 10.1016/j.ijepes.2014.04.028 Ghasemi, 2014, A novel hybrid algorithm of imperialistic competitive algorithm and teaching learning algorithm for optimal power flow problem with non-smooth cost functions, Eng. Appl. Artif. Intell., 29, 54, 10.1016/j.engappai.2013.11.003 Niknam, 2011, A modified shuffle frog leaping algorithm for multi-objective optimal power flow, Energy, 36, 6420, 10.1016/j.energy.2011.09.027 Sailaja Kumari, 2010, Enhanced Genetic Algorithm based computation technique for multi- objective optimal power flow solution, Electr. Power Energy Syst., 32, 736, 10.1016/j.ijepes.2010.01.010 Niknam, 2012, Improved particle swarm optimization for multi- objective optimal power flow considering the cost, loss, emission and voltage stability index, IET Generation Transm. Distribution, 6, 515, 10.1049/iet-gtd.2011.0851 Ippolito, 2014, Multi-objective optimized management of electrical energy storage systems in an island network with renewable energy sources under different design scenarios, Energy, 64, 648, 10.1016/j.energy.2013.11.065 Favuzza, 2011, 9 Graditi, 2015, Heuristic-based shiftable loads optimal management in smart micro-grids, IEEE Trans. Industrial Informatics, 11, 271, 10.1109/TII.2014.2331000 Abido, 2012, Multi-objective optimal power flow using differential evolution, Arabian J. Sci. Eng., 37, 991, 10.1007/s13369-012-0224-3 Coello, 1999, A comprehensive survey of evolutionary-based multi-objective optimization techniques, Knowl. Inf. Syst., 1, 269, 10.1007/BF03325101 Abido, 2003, Environmental/economic power dispatch using multi-objective evolutionary algorithms, IEEE Transac. Power Syst., 18, 1529, 10.1109/TPWRS.2003.818693 Andrew, 2010, Optimization of wind turbine energy and power factor with an evolutionary computation algorithm, Energy, 35, 1324, 10.1016/j.energy.2009.11.015 Abido, 2003, A novel multi objective evolutionary algorithm for environmental/economic power dispatch, Electr. Power Syst. Res., 65, 71, 10.1016/S0378-7796(02)00221-3 Niknam, 2013, A new optimization algorithm for multi- objective economic/emission dispatch, Electr. Power Energy Syst., 46, 283, 10.1016/j.ijepes.2012.10.001 Shabanpour-Haghighi, 2014, A modified teaching-learning based optimization for multi-objective optimal power flow problem, Energy Convers. Manag., 77, 597, 10.1016/j.enconman.2013.09.028 Ghasemi, 2014, Application of imperialistic competitive algorithm with its modified techniques for multi-objective optimal power flow problem: a comparative study, Inf. Sci., 281, 225, 10.1016/j.ins.2014.05.040 Chen, 2014, Multi-hive bee foraging algorithm for multi-objective optimal power flow considering the cost, loss and emission, Electr. Power Energy Syst., 60, 203, 10.1016/j.ijepes.2014.02.017 Panigrahi, 2010, Multiobjective fuzzy dominance based bacterial foraging algorithm to solve economic dispatch problem, Energy, 35, 4761, 10.1016/j.energy.2010.09.014 Niknam, 2013, Reserve constrained dynamic environmen- tal/economic dispatch: a new multiobjective self-adaptive learning bat algorithm, IEEE Syst. J., 7, 763, 10.1109/JSYST.2012.2225732 Azizipanah-Abarghooee, 2012, A new improved bat algorithm for fuzzy interactive multi-objective eco- nomic/emission dispatch with load and wind power uncertainty, 388 Azizipanah Abarghooee, 2011, Stochastic dynamic economic emission dispatch considering wind power, 158 Azizipanah-Abarghooee, 2015, Coordination of combined heat and power-thermal- wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods, Energy, 79, 50, 10.1016/j.energy.2014.10.024 Azizipanah-Abarghooee, 2014, Multi-objective short-term scheduling of thermo- electric power systems using a novel multi-objective θ-improved cuckoo optimisation algorithm, IET Generation Transm. Distribution, 8, 873, 10.1049/iet-gtd.2013.0354 Azizipanah-Abarghooee, 2014, Short-term scheduling of thermal power systems using hybrid gradient based modified teaching-learning optimizer with black hole algorithm, Electr. Power Syst. Res., 108, 16, 10.1016/j.epsr.2013.10.012 Azizipanah-Abarghooee, 2014, Modified shuffled frog leaping algo- rithm for multi-objective optimal power flow with FACTS devices, J. Intelligent Fuzzy Syst., 26, 681, 10.3233/IFS-120759 Srinivas, 1994, Multi objective optimization using non dominated sorting in genetic algorithms, Evol. Comput., 2, 221, 10.1162/evco.1994.2.3.221 Abido, 2003, A niched Pareto genetic algorithm for environmental/economic power dispatch, Electr. Power Syst. Res., 25, 97, 10.1016/S0142-0615(02)00027-3 Robert, 2004, 1 Kannan, 2009, Application of NSGA-II algorithm to generation expansion planning, IEEE Trans. Power Syst., 24, 454, 10.1109/TPWRS.2008.2004737 Zhao, 2005, Multiple objective particle swarm optimization technique for economic load dispatch, J. Zhejiang Univ. Sci., 6, 420, 10.1631/jzus.2005.A0420 Afzalan, 2014, An improved cuckoo search algorithm for power economic load dispatch, Int. Trans. Electr. Energy Syst. Basu, 2013, Cuckoo search algorithm for economic dispatch, Energy, 60, 99, 10.1016/j.energy.2013.07.011 El-Keib, 1990, Economic Dispatch in view of the clean AIR ACT of 1990, IEEE Trans. Power Syst., 9, 972, 10.1109/59.317648 Niknam, 2012, A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch, IEEE Trans. Power Syst., 28, 749, 10.1109/TPWRS.2012.2208273 Vaisakh, 2012, Solving dynamic economic dispatch problem with security constraints using bacterial foraging PSO-DE algorithm, Electr. power energy Syst., 39, 56, 10.1016/j.ijepes.2012.01.005 Kalyanmoy Deb, Samir Agarwal, Amrit Pratap, T. Meyarivan, A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II, Kanpur Genetic Algorithms Laboratory, IIT Kanpur. Dhillon, 1993, Stochastic economic emission load dispatch, Electr. Power Syst. Res., 26, 179, 10.1016/0378-7796(93)90011-3 http://en.wikipedia.org/wiki/Test_functions_for optimization. Abido, 2002, Optimal power flow using Tabu search algorithm, Electr. power components Syst., 30, 469, 10.1080/15325000252888425 Arul, 2013, Non-convex economic dispatch with heuristic load patterns, valve point loading effect, prohibited operating zones, ramp-rate limits, and spinning reserve constraints using harmony search algorithm, Electr. Eng., 95, 53, 10.1007/s00202-012-0241-y Zhu, 2001, Multi-area power systems economic dispatch using nonlinear convex network flow programming, Electr. Power Syst. Res., 59, 13, 10.1016/S0378-7796(01)00131-6