This paper reviews the researches on boiler combustion optimization, which is an important direction in the field of energy saving and emission reduction. Many methods have been used to deal with boiler combustion optimization, among which evolutionary computing (EC) techniques have recently gained much attention. However, the existing researches are not sufficiently focused and have not been summarized systematically. This has led to slow progress of research on boiler combustion optimization and has obstacles in the application. This paper introduces a comprehensive survey of the works of intelligent optimization algorithms in boiler combustion optimization and summarizes the contributions of different optimization algorithms. Finally, this paper discusses new research challenges and outlines future research directions, which can guide boiler combustion optimization to improve energy efficiency and reduce pollutant emission concentrations.
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This work was supported by the National Natural Science Foundation of China (Nos. 61806179, 61876169, 61922072, 61976237, 61673404, 62106230, 62006069, 62206255, and 62203332), China Postdoctoral Science Foundation (Nos. 2021T140616, 2021M692920, 2022M712878, and 2022TQ0298), Key R&D Projects of Ministry of Science and Technology (No. 2022YFD2001200), Key R&D and Promotion Projects in Henan Province (Nos. 192102210098 and 212102210510), and Henan Postdoctoral Foundation (No. 202003019).
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