End-of-life　(EOL)　product　recycling　has　received　increasing　attention　because　of　potential　environmental,　social　and　economic　benefits.　A　well-designed　reverse　supply　chain　(RSC)　can　efficiently　handle　EOL　products.　As　the　critical　activity　in　the　RSC,　the　disassembly　process　decomposes　collected　EOL　products　into　components　to　fulfill　the　demands　of　remanufacturing　plants.　Efficiently　coordinating　RSC　design　and　disassembly　line　balancing　decisions　may　improve　the　whole　system　performance　significantly,　especially　when　facing　multiple　EOL　products　and　uncertainty.　This　paper　investigates　a　novel　integrated　RSC　design　and　disassembly　line　balancing　problem　to　handle　multiple　EOL　products　where　the　supply　of　EOL　products,　the　demand　for　components,　and　task　times　in　disassembly　are　stochastic.　This　complex　problem　needs　to　jointly　determine　the　number　and　locations　of　disassembly　plants,　disassembly　equipment　procurement,　disassembly　line　balancing,　and　inventory　levels　of　both　EOL　products　collected　and　components　dismantled.　The　objectives　are　to　maximize　the　expected　profit　and　minimize　the　carbon　emissions　simultaneously.　For　the　problem,　a　bi-objective　two-stage　stochastic　programming　model　is　formulated　and　an　exact　epsilon-constrained　method　is　proposed,　transforming　the　bi-objective　problem　into　a　series　of　single-objective　problems.　Especially,　an　improved　Benders　decomposition　approach　is　developed　to　solve　each　single-objective　problem　efficiently.　Numerical　experiments　comprising　an　illustrative　case　and　200　random　instances　are　conducted　to　evaluate　the　performance　of　proposed　methods.　Moreover,　some　managerial　insights　are　drawn.