Purpose　This　paper　aims　to　solve　the　major　assessment　problem　in　matching　the　satisfaction　of　psychological　gratification　and　mission　accomplishment　pertaining　to　volunteers　with　the　disaster　rescue　and　recovery　tasks.　Design/methodology/approach　An　extended　belief　rule-based　(EBRB)　method　is　applied　with　the　method＇s　input　and　output　parameters　classified　based　on　expert　knowledge　and　data　from　literature.　These　parameters　include　volunteer　self-satisfaction,　experience,　peer-recognition,　and　cooperation.　First,　the　model　parameters　are　set;　then,　the　parameters　are　optimized　through　data　envelopment　analysis　(DEA)　and　differential　evolution　(DE)　algorithm.　Finally,　a　numerical　mountain　rescue　example　and　comparative　analysis　between　with-DEA　and　without-DEA　are　presented　to　demonstrate　the　efficiency　of　the　proposed　method.　The　proposed　model　is　suitable　for　a　two-way　matching　evaluation　between　rescue　tasks　and　volunteers.　Findings　Disasters　are　unexpected　events　in　which　emergency　rescue　is　crucial　to　human　survival.　When　a　disaster　occurs,　volunteers　provide　crucial　assistance　to　official　rescue　teams.　This　paper　finds　that　decision-makers　have　a　better　understanding　of　two-sided　match　objects　through　bilateral　feedback　over　time.　With　the　changing　of　the　matching　preference　information　between　rescue　tasks　and　volunteers,　the　satisfaction　of　volunteer＇s　psychological　gratification　and　mission　accomplishment　are　also　constantly　changing.　Therefore,　considering　matching　preference　information　and　satisfaction　at　two-sided　match　objects　simultaneously　is　necessary　to　get　reasonable　target　values　of　matching　results　for　rescue　tasks　and　volunteers.　Originality/value　Based　on　the　authors＇　novel　EBRB　method,　a　matching　assessment　model　is　constructed,　with　two-sided　matching　of　volunteers　to　rescue　tasks.　This　method　will　provide　matching　suggestions　in　the　field　of　emergency　dispatch　and　contribute　to　the　assessment　of　emergency　plans　around　the　world.