To　decrease　pollutant　emissions,　improve　main　steam　flow　and　its　stability,　and　reduce　operating　costs　of　the　municipal　solid　waste　incineration　(MSWI)　process,　a　dynamic　multiobjective　optimization　(DMO)　method　for　the　MSWI　process　is　proposed　in　this　paper.　First,　the　dynamic　performance　indices　of　nitrogen　oxides　(NOx),　sulfur　dioxide　(SO2),　and　hydrogen　chloride　(HCl)　emissions,　and　main　steam　flow　are　established　using　data-driven　method.　Second,　a　novel　dual　archive　multiobjective　competitive　swarm　optimization　(daMCSO)　algorithm　is　proposed　to　solve　the　DMO　problem　of　the　MSWI　process.　An　optimization　strategy　is　designed　to　enhance　the　search　ability　of　the　population,　and　a　dual　archive　scheme　is　proposed　to　realize　optimization　requirements　on　the　decision　preferences.　Finally,　a　real　industrial　data　set　is　used　for　the　experimental　studies,　and　the　results　show　that　the　NOx,　SO2,　and　HCl　emission　concentrations　reduce　by　11.91%,　12.17%,　and　12.09%　respectively,　the　main　stram　flow　increases　by　4.45%　and　its　stability　improves　by　20.59%,　and　the　usage　of　urea　solution　and　limestone　slurry　decreases　by　9.40%　and　20.43%.　©　2024　Copyright　held　by　the　owner/author(s).