ARCHIVES
Year 2026 · Volume 6 · Issue 5
Original Article
Lévy Opposition-Based Learning Bat Algorithm for Combined Economic and Emission Dispatch
Mallikarjuna Bestha1
Y. V. Siva Reddy2
R. Kiranmayi3
1 Research Scholar, JNTUA, Department of EEE, Ananthapuramu, Andhra Pradesh, India. 2 Professor, Department of EEE, G. Pulla Reddy Engineering College, Kurnool, Andhra Pradesh, India. 3 Professor, Department of EEE, JNTUA, Ananthapuramu, Andhra Pradesh, India.
Published Online: September-October 2026
Pages: 01-12
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20260605001
References
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[6]. O. Ajay and ReolynHeymann, “Day-Ahead Combined Economic and Emission Dispatch with Spinning Reserve Consideration Using Moth Swarm Algorithm for A Data Centre Load,” Heliyon, vol. 7, no. 9, Sep. 2021, doi: 10.1016/j.heliyon.2021.e08054.
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[13]. A. Srivastava, D. K. Das, and P. K. Gupta, “A quantum class topper optimization algorithm to solve combined emission economic dispatch problem,” Evol Intell, vol. 15, no. 1, pp. 513–527, Mar. 2022, doi: 10.1007/s12065-020-00526-1.
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[15]. M. Sutar and H. T. Jadhav, “A modified artificial bee colony algorithm based on a non-dominated sorting genetic approach for combined economic-emission load dispatch problem,” Appl Soft Comput, vol. 144, Sep. 2023, doi: 10.1016/j.asoc.2023.110433.
[16]. C. Lin, H. Liang, and A. Pang, “A fast data-driven optimization method of multi-area combined economic emission dispatch,” Appl Energy, vol. 337, May 2023, doi: 10.1016/j.apenergy.2023.120884.
[17]. Y. P. Li, L. X. Zhang, and Z. J. Feng, “Arithmetic Optimization Algorithm Based on Cauchy Mutation Trigonometric Function Search to Solve Combined Economic Emission Dispatch Problem,” IEEE Access, vol. 11, pp. 136885–136909, 2023, doi: 10.1109/ACCESS.2023.3338160.
[18]. T. R. Manikandan and V. Thangavelu, “Combined Economic and Emission Power Dispatch Control Using Substantial Augmented Transformative Algorithm,” Intelligent Automation and Soft Computing, vol. 35, no. 1, pp. 431–447, 2023, doi: 10.32604/iasc.2023.026546.
[19]. W. K. Hao et al., “Multi-objective arithmetic optimization algorithm with random searching strategies to solve combined economic emission dispatch problem,” Comput Ind Eng, vol. 195, Sep. 2024, doi: 10.1016/j.cie.2024.110434.
[20]. R. Z. Khlaif and T. H. Atyia, “Comparative analysis of optimization approaches for combined economic emission dispatch- a comprehensive review,” Engineering Research Express, vol. 6, no. 3, Sep. 2024, doi: 10.1088/2631-8695/ad7783.
[21]. M. Gajić et al., “Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-Parametric Tests,” Applied Artificial Intelligence, vol. 38, no. 1, 2024, doi: 10.1080/08839514.2024.2322335.
[22]. C. Lin, H. Liang, A. Pang, J. Zhong, and Y. Yang, “Data-Driven Surrogate-Assisted Method for High-Dimensional Multi-Area Combined Economic/Emission Dispatch,” Journal of Modern Power Systems and Clean Energy, vol. 12, no. 1, pp. 52–64, Jan. 2024, doi: 10.35833/MPCE.2023.000128.
[23]. M. Asif et al., “Combined emission economic dispatch using quantum-inspired particle swarm optimization and its variants,” Energy Exploration and Exploitation, vol. 42, no. 5, pp. 1602–1644, Sep. 2024, doi: 10.1177/01445987241235419.
[24]. S. Muraleedharan, C. A. Babu, and A. Kumar Sasidharanpillai, “Chi-square mutated quantum-behaved PSO algorithm for combined economic and emission dispatch,” Evol Intell, vol. 17, no. 5–6, pp. 3961–3984, Oct. 2024, doi: 10.1007/s12065-024-00966-z.
[25]. F. Wang, S. Bi, S. Feng, H. Zhang, and C. Guo, “Combined economic and emission power dispatch problems through multi-objective Honey Badger optimizer,” Cluster Comput, vol. 27, no. 7, pp. 9887–9915, Oct. 2024, doi: 10.1007/s10586-024-04345-2.
[26]. Y. X. Li, J. S. Wang, X. Y. Guan, X. T. Wang, X. Liu, and S. B. Zhang, “Arithmetic optimization algorithm with three-dimensional chaotic mapping in spherical coordinate system for combined economic emission dispatch problem,” Appl Energy, vol. 380, Feb. 2025, doi: 10.1016/j.apenergy.2024.124953.
[27]. Y. Wang, X. Yu, and W. Zhang, “An improved reinforcement learning-based differential evolution algorithm for combined economic and emission dispatch problems,” Eng Appl Artif Intell, vol. 140, Jan. 2025, doi: 10.1016/j.engappai.2024.109709.
[28]. X. Yu, Y. Wang, and W. Zhang, “A dueling double deep Q network assisted cooperative dual-population coevolutionary algorithm for multi-objective combined economic and emission dispatch problems,” Swarm Evol Comput, vol. 95, Jun. 2025, doi: 10.1016/j.swevo.2025.101949.
[29]. A. Arkwaee and R. Ali Abttan, “Enhanced Zebra Optimization Algorithm for Sustainable Combined Economic and Emission Dispatch in Power Systems,” Array, p. 100484, Sep. 2025, doi: 10.1016/j.array.2025.100484.
[30]. X. Y. Zhang, J. S. Wang, J. H. Zhu, Y. Y. Bao, Y. Zheng, and W. K. Hao, “Nonlinear convergence factor-based manta ray foraging optimization algorithm for combined economic emission dispatch problem,” Soft comput, vol. 29, no. 2, pp. 1053–1089, Jan. 2025, doi: 10.1007/s00500-025-10402-8.
[31]. K. Y. Chan, K. F. C. Yiu, and D. Kim, “An Epsilon constraint-based evolutionary algorithm and multi-objective quality metrics for combined economic emission dispatch problem,” Aug. 01, 2025, Springer Science and Business Media Deutschland GmbH. doi: 10.1007/s00521-025-11330-2.
[32]. X.S. Yang, “A New Metaheuristic Bat-Inspired Algorithm,” in Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), J. R. González, D. A. Pelta, C. Cruz, G. Terrazas, and N. Krasnogor, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 65–74. doi: 10.1007/978-3-642-12538-6_6.
[33]. N. C. Yang and M. D. Le, “Multi-objective bat algorithm with time-varying inertia weights for optimal design of passive power filters set,” IET Generation, Transmission and Distribution, vol. 9, no. 7, pp. 644–654, Apr. 2015, doi: 10.1049/iet-gtd.2014.0965.
[34]. H. R. Tizhoosh, “Opposition-Based Learning: A New Scheme for Machine Intelligence,” in International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC’06), 2005, pp. 695–701. doi: 10.1109/CIMCA.2005.1631345.
[35]. W. Long, J. Jiao, X. Liang, S. Cai, and M. Xu, “A Random Opposition-Based Learning Grey Wolf Optimizer,” IEEE Access, vol. 7, pp. 113810–113825, 2019, doi: 10.1109/ACCESS.2019.2934994.
[36]. S. Mirjalili and A. Lewis, “The Whale Optimization Algorithm,” Advances in Engineering Software, vol. 95, pp. 51–67, May 2016, doi: 10.1016/j.advengsoft.2016.01.008.
[37]. X.S. Yang, “Flower Pollination Algorithm for Global Optimization,” in Unconventional Computation and Natural Computation, J. Durand-Lose and N. Jonoska, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 240–249.
[38]. S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, 2014, doi: 10.1016/j.advengsoft.2013.12.007.
[39]. S. Mirjalili, S. M. Mirjalili, and A. Hatamlou, “Multi-Verse Optimizer: a nature-inspired algorithm for global optimization,” Neural Comput Appl, vol. 27, no. 2, pp. 495–513, Feb. 2016, doi: 10.1007/s00521-015-1870-7.
[40]. S. Mirjalili, “SCA: A Sine Cosine Algorithm for solving optimization problems,” Knowl Based Syst, vol. 96, pp. 120–133, Mar. 2016, doi: 10.1016/j.knosys.2015.12.022.[41]. L. Abualigah, A. Diabat, S. Mirjalili, M. Abd Elaziz, and A. H. Gandomi, “The Arithmetic Optimization Algorithm,” Comput Methods Appl Mech Eng, vol. 376, Apr. 2021, doi: 10.1016/j.cma.2020.113609.
[42]. T. S. L. V. Ayyarao et al., “War Strategy Optimization Algorithm: A New Effective Metaheuristic Algorithm for Global Optimization,” IEEE Access, vol. 10, pp. 25073–25105, 2022, doi: 10.1109/ACCESS.2022.3153493.
[43]. H. Su et al., “RIME: A physics-based optimization,” Neurocomputing, vol. 532, pp. 183–214, May 2023, doi: 10.1016/J.NEUCOM.2023.02.010.
[44]. S. Krishnamurthy and R. Tzoneva, “Impact of price penalty factors on the solution of the combined economic emission dispatch problem using cubic criterion functions,” in 2012 IEEE Power and Energy Society General Meeting, 2012, pp. 1–9. doi: 10.1109/PESGM.2012.6345312.
[45]. F. P. Mahdi, P. Vasant, M. Abdullah-Al-Wadud, J. Watada, V. Kallimani, and P. Y. S. Fai, “Quantum particle swarm optimization for economic dispatch problem using cubic function considering power loss constraint,” International Journal of GEOMATE, vol. 13, no. 7, pp. 44–50, 2017, doi: 10.21660/2017.37.2742.
[46]. Ziane, F. Benhamida, and A. Graa, “Simulated annealing algorithm for combined economic and emission power dispatch using max/max price penalty factor,” Neural Comput Appl, vol. 28, pp. 197–205, Dec. 2017, doi: 10.1007/s00521-016-2335-3.
[47]. F. P. Mahdi, P. Vasant, M. Abdullah-Al-Wadud, V. Kallimani, and J. Watada, “Quantum-behaved bat algorithm for many-objective combined economic emission dispatch problem using cubic criterion function,” Neural Comput Appl, vol. 31, no. 10, pp. 5857–5869, Oct. 2019, doi: 10.1007/s00521-018-3399-z.
[48]. D. Gonidakis and A. Vlachos, “A new sine cosine algorithm for economic and emission dispatch problems with price penalty factors,” Journal of Information and Optimization Sciences, vol. 40, no. 3, pp. 679–697, Apr. 2019, doi: 10.1080/02522667.2018.1453667
[2]. M. A. El-Shorbagy and A. A. Mousa, “Constrained Multiobjective Equilibrium Optimizer Algorithm for Solving Combined Economic Emission Dispatch Problem,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/6672131.
[3]. B. Dey, S. Basak, and B. Bhattacharyya, “A comparative analysis between price-penalty factor method and fractional programming method for combined economic emission dispatch problem using novel hybrid CSA-JAYA algorithm,” IET Smart Grid, vol. 4, no. 4, pp. 367–380, Aug. 2021, doi: 10.1049/stg2.12037.
[4]. M. H. Hassan, S. Kamel, S. Q. Salih, T. Khurshaid, and M. Ebeed, “Developing chaotic artificial ecosystem-based optimization algorithm for combined economic emission dispatch,” IEEE Access, vol. 9, pp. 51146–51165, 2021, doi: 10.1109/ACCESS.2021.3066914.
[5]. S. Fayyaz et al., “Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm,” IEEE Access, vol. 9, pp. 56152–56167, 2021, doi: 10.1109/ACCESS.2021.3072012.
[6]. O. Ajay and ReolynHeymann, “Day-Ahead Combined Economic and Emission Dispatch with Spinning Reserve Consideration Using Moth Swarm Algorithm for A Data Centre Load,” Heliyon, vol. 7, no. 9, Sep. 2021, doi: 10.1016/j.heliyon.2021.e08054.
[7]. M. H. Hassan, D. Yousri, S. Kamel, and C. Rahmann, “A modified Marine predators algorithm for solving single- and multi-objective combined economic emission dispatch problems,” Comput Ind Eng, vol. 164, Feb. 2022, doi: 10.1016/j.cie.2021.107906.
[8]. W. K. Hao, J. S. Wang, X. D. Li, H. M. Song, and Y. Y. Bao, “Probability distribution arithmetic optimization algorithm based on variable order penalty functions to solve combined economic emission dispatch problem,” Appl Energy, vol. 316, Jun. 2022, doi: 10.1016/j.apenergy.2022.119061.
[9]. P. Mohapatra, “Combined economic emission dispatch in hybrid power systems using competitive swarm optimization,” Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 10, pp. 8955–8971, Nov. 2022, doi: 10.1016/j.jksuci.2022.08.022.
[10]. S. Zaoui and A. Belmadani, “Solution of combined economic and emission dispatch problems of power systems without penalty,” Applied Artificial Intelligence, vol. 36, no. 1, 2022, doi: 10.1080/08839514.2021.1976092.[11]. P. Verma and R. P. Parouha, “An innovative hybrid algorithm for solving combined economic and emission dispatch problems,” Soft comput, vol. 26, no. 22, pp. 12635–12666, Nov. 2022, doi: 10.1007/s00500-022-07262-x.
[12]. S. Basak, B. Bhattacharyya, and B. Dey, “Combined economic emission dispatch on dynamic systems using hybrid CSA-JAYA Algorithm,” International Journal of System Assurance Engineering and Management, vol. 13, no. 5, pp. 2269–2290, Oct. 2022, doi: 10.1007/s13198-022-01635-z.
[13]. A. Srivastava, D. K. Das, and P. K. Gupta, “A quantum class topper optimization algorithm to solve combined emission economic dispatch problem,” Evol Intell, vol. 15, no. 1, pp. 513–527, Mar. 2022, doi: 10.1007/s12065-020-00526-1.
[14]. W. Luo, X. Yu, and Y. Wei, “Solving combined economic and emission dispatch problems using reinforcement learning-based adaptive differential evolution algorithm,” Eng Appl Artif Intell, vol. 126, Nov. 2023, doi: 10.1016/j.engappai.2023.107002.
[15]. M. Sutar and H. T. Jadhav, “A modified artificial bee colony algorithm based on a non-dominated sorting genetic approach for combined economic-emission load dispatch problem,” Appl Soft Comput, vol. 144, Sep. 2023, doi: 10.1016/j.asoc.2023.110433.
[16]. C. Lin, H. Liang, and A. Pang, “A fast data-driven optimization method of multi-area combined economic emission dispatch,” Appl Energy, vol. 337, May 2023, doi: 10.1016/j.apenergy.2023.120884.
[17]. Y. P. Li, L. X. Zhang, and Z. J. Feng, “Arithmetic Optimization Algorithm Based on Cauchy Mutation Trigonometric Function Search to Solve Combined Economic Emission Dispatch Problem,” IEEE Access, vol. 11, pp. 136885–136909, 2023, doi: 10.1109/ACCESS.2023.3338160.
[18]. T. R. Manikandan and V. Thangavelu, “Combined Economic and Emission Power Dispatch Control Using Substantial Augmented Transformative Algorithm,” Intelligent Automation and Soft Computing, vol. 35, no. 1, pp. 431–447, 2023, doi: 10.32604/iasc.2023.026546.
[19]. W. K. Hao et al., “Multi-objective arithmetic optimization algorithm with random searching strategies to solve combined economic emission dispatch problem,” Comput Ind Eng, vol. 195, Sep. 2024, doi: 10.1016/j.cie.2024.110434.
[20]. R. Z. Khlaif and T. H. Atyia, “Comparative analysis of optimization approaches for combined economic emission dispatch- a comprehensive review,” Engineering Research Express, vol. 6, no. 3, Sep. 2024, doi: 10.1088/2631-8695/ad7783.
[21]. M. Gajić et al., “Behavior Analysis of the New PSO-CGSA Algorithm in Solving the Combined Economic Emission Dispatch Using Non-Parametric Tests,” Applied Artificial Intelligence, vol. 38, no. 1, 2024, doi: 10.1080/08839514.2024.2322335.
[22]. C. Lin, H. Liang, A. Pang, J. Zhong, and Y. Yang, “Data-Driven Surrogate-Assisted Method for High-Dimensional Multi-Area Combined Economic/Emission Dispatch,” Journal of Modern Power Systems and Clean Energy, vol. 12, no. 1, pp. 52–64, Jan. 2024, doi: 10.35833/MPCE.2023.000128.
[23]. M. Asif et al., “Combined emission economic dispatch using quantum-inspired particle swarm optimization and its variants,” Energy Exploration and Exploitation, vol. 42, no. 5, pp. 1602–1644, Sep. 2024, doi: 10.1177/01445987241235419.
[24]. S. Muraleedharan, C. A. Babu, and A. Kumar Sasidharanpillai, “Chi-square mutated quantum-behaved PSO algorithm for combined economic and emission dispatch,” Evol Intell, vol. 17, no. 5–6, pp. 3961–3984, Oct. 2024, doi: 10.1007/s12065-024-00966-z.
[25]. F. Wang, S. Bi, S. Feng, H. Zhang, and C. Guo, “Combined economic and emission power dispatch problems through multi-objective Honey Badger optimizer,” Cluster Comput, vol. 27, no. 7, pp. 9887–9915, Oct. 2024, doi: 10.1007/s10586-024-04345-2.
[26]. Y. X. Li, J. S. Wang, X. Y. Guan, X. T. Wang, X. Liu, and S. B. Zhang, “Arithmetic optimization algorithm with three-dimensional chaotic mapping in spherical coordinate system for combined economic emission dispatch problem,” Appl Energy, vol. 380, Feb. 2025, doi: 10.1016/j.apenergy.2024.124953.
[27]. Y. Wang, X. Yu, and W. Zhang, “An improved reinforcement learning-based differential evolution algorithm for combined economic and emission dispatch problems,” Eng Appl Artif Intell, vol. 140, Jan. 2025, doi: 10.1016/j.engappai.2024.109709.
[28]. X. Yu, Y. Wang, and W. Zhang, “A dueling double deep Q network assisted cooperative dual-population coevolutionary algorithm for multi-objective combined economic and emission dispatch problems,” Swarm Evol Comput, vol. 95, Jun. 2025, doi: 10.1016/j.swevo.2025.101949.
[29]. A. Arkwaee and R. Ali Abttan, “Enhanced Zebra Optimization Algorithm for Sustainable Combined Economic and Emission Dispatch in Power Systems,” Array, p. 100484, Sep. 2025, doi: 10.1016/j.array.2025.100484.
[30]. X. Y. Zhang, J. S. Wang, J. H. Zhu, Y. Y. Bao, Y. Zheng, and W. K. Hao, “Nonlinear convergence factor-based manta ray foraging optimization algorithm for combined economic emission dispatch problem,” Soft comput, vol. 29, no. 2, pp. 1053–1089, Jan. 2025, doi: 10.1007/s00500-025-10402-8.
[31]. K. Y. Chan, K. F. C. Yiu, and D. Kim, “An Epsilon constraint-based evolutionary algorithm and multi-objective quality metrics for combined economic emission dispatch problem,” Aug. 01, 2025, Springer Science and Business Media Deutschland GmbH. doi: 10.1007/s00521-025-11330-2.
[32]. X.S. Yang, “A New Metaheuristic Bat-Inspired Algorithm,” in Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), J. R. González, D. A. Pelta, C. Cruz, G. Terrazas, and N. Krasnogor, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 65–74. doi: 10.1007/978-3-642-12538-6_6.
[33]. N. C. Yang and M. D. Le, “Multi-objective bat algorithm with time-varying inertia weights for optimal design of passive power filters set,” IET Generation, Transmission and Distribution, vol. 9, no. 7, pp. 644–654, Apr. 2015, doi: 10.1049/iet-gtd.2014.0965.
[34]. H. R. Tizhoosh, “Opposition-Based Learning: A New Scheme for Machine Intelligence,” in International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC’06), 2005, pp. 695–701. doi: 10.1109/CIMCA.2005.1631345.
[35]. W. Long, J. Jiao, X. Liang, S. Cai, and M. Xu, “A Random Opposition-Based Learning Grey Wolf Optimizer,” IEEE Access, vol. 7, pp. 113810–113825, 2019, doi: 10.1109/ACCESS.2019.2934994.
[36]. S. Mirjalili and A. Lewis, “The Whale Optimization Algorithm,” Advances in Engineering Software, vol. 95, pp. 51–67, May 2016, doi: 10.1016/j.advengsoft.2016.01.008.
[37]. X.S. Yang, “Flower Pollination Algorithm for Global Optimization,” in Unconventional Computation and Natural Computation, J. Durand-Lose and N. Jonoska, Eds., Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp. 240–249.
[38]. S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46–61, 2014, doi: 10.1016/j.advengsoft.2013.12.007.
[39]. S. Mirjalili, S. M. Mirjalili, and A. Hatamlou, “Multi-Verse Optimizer: a nature-inspired algorithm for global optimization,” Neural Comput Appl, vol. 27, no. 2, pp. 495–513, Feb. 2016, doi: 10.1007/s00521-015-1870-7.
[40]. S. Mirjalili, “SCA: A Sine Cosine Algorithm for solving optimization problems,” Knowl Based Syst, vol. 96, pp. 120–133, Mar. 2016, doi: 10.1016/j.knosys.2015.12.022.[41]. L. Abualigah, A. Diabat, S. Mirjalili, M. Abd Elaziz, and A. H. Gandomi, “The Arithmetic Optimization Algorithm,” Comput Methods Appl Mech Eng, vol. 376, Apr. 2021, doi: 10.1016/j.cma.2020.113609.
[42]. T. S. L. V. Ayyarao et al., “War Strategy Optimization Algorithm: A New Effective Metaheuristic Algorithm for Global Optimization,” IEEE Access, vol. 10, pp. 25073–25105, 2022, doi: 10.1109/ACCESS.2022.3153493.
[43]. H. Su et al., “RIME: A physics-based optimization,” Neurocomputing, vol. 532, pp. 183–214, May 2023, doi: 10.1016/J.NEUCOM.2023.02.010.
[44]. S. Krishnamurthy and R. Tzoneva, “Impact of price penalty factors on the solution of the combined economic emission dispatch problem using cubic criterion functions,” in 2012 IEEE Power and Energy Society General Meeting, 2012, pp. 1–9. doi: 10.1109/PESGM.2012.6345312.
[45]. F. P. Mahdi, P. Vasant, M. Abdullah-Al-Wadud, J. Watada, V. Kallimani, and P. Y. S. Fai, “Quantum particle swarm optimization for economic dispatch problem using cubic function considering power loss constraint,” International Journal of GEOMATE, vol. 13, no. 7, pp. 44–50, 2017, doi: 10.21660/2017.37.2742.
[46]. Ziane, F. Benhamida, and A. Graa, “Simulated annealing algorithm for combined economic and emission power dispatch using max/max price penalty factor,” Neural Comput Appl, vol. 28, pp. 197–205, Dec. 2017, doi: 10.1007/s00521-016-2335-3.
[47]. F. P. Mahdi, P. Vasant, M. Abdullah-Al-Wadud, V. Kallimani, and J. Watada, “Quantum-behaved bat algorithm for many-objective combined economic emission dispatch problem using cubic criterion function,” Neural Comput Appl, vol. 31, no. 10, pp. 5857–5869, Oct. 2019, doi: 10.1007/s00521-018-3399-z.
[48]. D. Gonidakis and A. Vlachos, “A new sine cosine algorithm for economic and emission dispatch problems with price penalty factors,” Journal of Information and Optimization Sciences, vol. 40, no. 3, pp. 679–697, Apr. 2019, doi: 10.1080/02522667.2018.1453667
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