Municipal　solid　waste　incineration　(MSWI)　becomes　the　most　popular　technique　to　enhance　environment　protection.　This　process　produces　one　of　the　most　toxic　chemicals　in　the　world,　i.e.,　polychlorinated　dibenzo-p-dioxins　and　polychlorinated　dibenzofurans　(PCDD/Fs).　The　dioxin　(DXN)　production　should　be　restricted　rigidly　by　using　operation　optimization　and　control　of　MSWI　process　based　on　present　industrial　devices.　However,　it　is　difficult　to　realize　the　on-line　real-time　continuous　measuring　of　DXN　duo　to　the　complexity　formation　mechanism　and　high-cost　long-time　off-line　detection　approach.　In　this　paper,　a　soft　measuring　method　based　on　virtual　sample　generation　(VSG)　is　used　to　address　this　problem　at　the　first　time.　A　few　numbers　of　true　training　samples　are　used　to　produce　virtual　training　samples　based　on　feasibility-based　programming　(FBP)　model　using　selective　ensemble　kernel　partial　least　squares　(SENKPLS)　and　prior　knowledge.　Simulation　result　based　on　dataset　in　reference　[31]　for　a　HL　MSWI　process　shows　effectiveness　of　the　proposed　method.