International Journal of Mathematical Sciences and Computing (IJMSC)
IJMSC Vol. 12, No. 2, 8 Jun. 2026
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A Novel Intuitionistic Fuzzy Algorithm to the Evaluation of Emission and Economic Load Dispatch Problem
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Author(s)
Index Terms
Fuzzy Optimization, Economic and Emission Dispatching, Intuitionistic Fuzzy Optimization, Power System Optimization
Abstract
This research uses an advanced intuitionistic fuzzy optimization framework to study the Multi-Objective Emission and Economic Load Dispatch (MEELD) issue under ambiguous and imprecise operational conditions. Because fuel cost and pollution emissions must be minimized simultaneously while carefully adhering to power balancing calculations, generator capacity limitations, and system operational constraints, the MEELD problem is intrinsically complicated. A strong optimization method that can manage uncertainty and decision ambiguity is required because of these competing goals. In order to overcome this difficulty, a mathematical model that incorporates vagueness related to system characteristics and decision variables is developed in both fuzzy and intuitionistic fuzzy contexts. The intuitionistic fuzzy model, in contrast to other fuzzy methods, takes membership, non-membership, and hesitation degrees into account, offering a more thorough depiction of uncertainty. Using intuitionistic fuzzy aggregation operators, a structured solution approach is suggested to convert the multi-objective optimization problem into an equivalent single-objective formulation. A three-unit thermal power generation system, which is frequently used as a benchmark in MEELD research, is used to illustrate the efficacy of the suggested methodology. The intuitionistic fuzzy optimization method effectively accomplishes an ideal trade-off between economic and environmental goals, according to simulation data. When compared to conventional optimization techniques, the resulting solutions show better compromise solutions, increased flexibility, and improved convergence characteristics. In summary, the MEELD problem continues to be a crucial component of contemporary power system operation, especially when considering sustainable energy management and environmental requirements. For large-scale power system applications needing simultaneous economic and emission optimization, the suggested intuitionistic fuzzy optimization approach offers a technically sound and effective framework for decision-making.
Cite This Paper
Prabir Kumar Sarkar, Samir Dey, "A Novel Intuitionistic Fuzzy Algorithm to the Evaluation of Emission and Economic Load Dispatch Problem", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.12, No.2, pp. 19-33, 2026. DOI: 10.5815/ijmsc.2026.02.02
Reference
[1]S. Z. Li and A. K. Ja[1]L. J. Gent MR, “Minimum-emission dispatch.,” IEEE Trans Power Appar Syst, vol. 90, no. 6, pp. 2650–2660, 1971.
[2]J. Nanda, D. P. Kothari, and K. S. Lingamurthy, “Economic-emission load dispatch through goal programming techniques,” IEEE Trans. Energy Convers., vol. 3, no. 1, pp. 26–32, 1988, doi: 10.1109/60.4195.
[3]N. Thenmozhi and D. Mary, “Economic emission load dispatch using hybrid Genetic Algorithm,” IEEE Reg. 10 Annu. Int. Conf. Proceedings/TENCON, vol. C, 2004, doi: 10.1109/tencon.2004.1414811.
[4]R. E. Pérez-Guerrero and J. R. Cedeño-Maldonado, “Differential evolution based economic environmental power dispatch,” Proc. 37th Annu. North Am. Power Symp. 2005, vol. 2005, pp. 191–197, 2005, doi: 10.1109/NAPS.2005.1560523.
[5]A. Bhattacharya and P. K. Chattopadhyay, “Oppositional Biogeography-Based Optimization for multi-objective Economic Emission Load Dispatch,” Proc. 2010 Annu. IEEE India Conf. Green Energy, Comput. Commun. INDICON 2010, vol. 38, no. 3, pp. 340–365, 2010, doi: 10.1109/INDCON.2010.5712607.
[6]S. Kumar, V. Kumar, N. Katal, S. K. Singh, S. Sharma, and P. Singh, “Multiarea Economic Dispatch Using Evolutionary Algorithms,” Math. Probl. Eng., vol. 2021, pp. 1–14, 2021, doi: 10.1155/2021/3577087.
[7]M. Dashtdar et al., “Solving the environmental/economic dispatch problem using the hybrid FA-GA multi-objective algorithm,” Energy Reports, vol. 8, pp. 13766–13779, Nov. 2022, doi: 10.1016/J.EGYR.2022.10.054.
[8]N. Singh et al., “A New PSO Technique Used for the Optimization of Multiobjective Economic Emission Dispatch,” Electron. 2023, Vol. 12, Page 2960, vol. 12, no. 13, p. 2960, Jul. 2023, doi: 10.3390/ELECTRONICS12132960.
[9]M. Shafiee, A.-A. Zamani, and M. Sajadinia, “Using Improved DDAO Algorithm to Solve Economic Emission Load Dispatch Problem in the Presence of Wind Farms,” Int. J. Ind. Electron. Control Optim., vol. 6, no. 3, pp. 161–169, Sep. 2023, doi: 10.22111/IECO.2023.45189.1470.
[10]S. K. Mishra, V. K. Gupta, R. Kumar, S. K. Swain, and D. K. Mohanta, “Multi-objective optimization of economic emission load dispatch incorporating load forecasting and solar photovoltaic sources for carbon neutrality,” Electr. Power Syst. Res., vol. 223, p. 109700, Oct. 2023, doi: 10.1016/J.EPSR.2023.109700.
[11]M. Chandrashekhar and P. K.Dhal, “Combined economic and emission dispatch using Whale Optimization Algorithm,” ARPN J. Eng. Appl. Sci., pp. 2692–2707, 2024, doi: 10.59018/1223321.
[12]Y. Gao et al., “Economic Dispatch Optimization Strategies and Problem Formulation: A Comprehensive Review,” Energies 2024, Vol. 17, Page 550, vol. 17, no. 3, p. 550, Jan. 2024, doi: 10.3390/EN17030550.
[13]L. A. Zadeh, “Fuzzy sets,” Inf. Control, vol. 8, no. 3, pp. 338–353, 1965, doi: 10.1016/s0019-9958(65)90241-x.
[14]H.-J. Zimmermann, “Fuzzy programming and linear programming with several objective functions,” Fuzzy Sets Syst., vol. 1, no. 1, pp. 45–55, 1978, doi: 10.1016/0165-0114(78)90031-3.
[15]K. T. Atanassov, “Intuitionistic fuzzy sets,” Fuzzy Sets Syst., vol. 20, no. 1, pp. 87–96, 1986, doi: 10.1016/s0165-0114(86)80034-3.
[16]P. P. Angelov, “Optimization in an intuitionistic fuzzy environment,” Fuzzy Sets Syst., vol. 86, no. 3, pp. 299–306, Mar. 1997, doi: 10.1016/S0165-0114(96)00009-7.
[17]S. Gupta, A. Haq, I. Ali, and B. Sarkar, “Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment,” Complex Intell. Syst., vol. 7, no. 4, pp. 2119–2139, 2021, doi: 10.1007/s40747-021-00326-9.
[18]V. P. Singh, K. Sharma, D. Chakraborty, and A. Ebrahimnejad, “A novel multi-objective bi-level programming problem under intuitionistic fuzzy environment and its application in production planning problem,” Complex Intell. Syst., vol. 8, no. 4, pp. 3263–3278, 2022, doi: 10.1007/s40747-022-00662-4.
[19]K. Sharma, V. Singh, A. Ebrahimnejad, and D. Chakraborty, “A Novel Multi-Objective Linear Fractional Optimization Model in Intuitionistic Fuzzy Environment and its Application in Organization Planning,” SSRN Electron. J., 2022, doi: 10.2139/ssrn.4054426.
[20]S. Pawar, P. Patel, and A. B. Mirajkar, “Relevance of Intuitionistic Fuzzy Optimization Approach in Planning of a Multi–Objective Water Resource System,” Water Resour. Manag., vol. 38, no. 8, pp. 2935–2959, 2024, doi: 10.1007/s11269-024-03799-8.
[21]K. T. Atanassov, “Two theorems for intuitionistic fuzzy sets,” Fuzzy Sets Syst., vol. 110, no. 2, pp. 267–269, 2000, doi: 10.1016/s0165-0114(99)00112-8.
[22]P. P. Angelov, “Optimization in an intuitionistic fuzzy environment,” Fuzzy Sets Syst., vol. 86, no. 3, pp. 299–306, 1997, doi: 10.1016/s0165-0114(96)00009-7.
[23]S. G. and K. R. S.Dey, A.Ray, “Economic Load Dispatch Model Optimization using Fuzzy Interactive Optimization Technique,” Int. J. Comput. Sci. Eng., vol. 7, no. specisl Issue 18, 2019.
[24]P. K.Sarkar and S. Dey, “Multi-objective Economic Environmental Power Dispatch (EEPD) Model Optimization: A Novel Approach,” in Proceedings of National Seminar On Recent Advances in Interdisciplinary Science & Research – 2025, 2025, p. 71.
[25]W. F. A. El-Wahed, “A multi-objective transportation problem under fuzziness,” Fuzzy Sets Syst., vol. 117, no. 1, pp. 27–33, 2001, doi: 10.1016/S0165-0114(98)00155-9.