To　find　the　optimal　shielding　design　for　compact　accelerator-driven　neutron　sources　(CANS)　using　multiobjective　optimization,　we　developed　a　new　method　called　nondominated　sorting　genetic　algorithm-Monte　Carlo　method　(NSGA-MC).　NSGA-MC　employs　NSGA-II　to　optimize　the　shielding　parameters　based　on　calculations　made　by　the　Monte　Carlo　N-Particle　Transport　Code　(MCNP).　A　layered　shielding　configuration　with　two　materials　of　borated　polyethylene　(BPE)　and　lead　(Pb)　in　the　order　of　BPE/Pb/BPE/Pb　for　RIKEN　Accelerator-driven　Compact　Neutron　Source　(RANS)　was　examined　using　this　method,　and　two　objectives　were　optimized　simultaneously:　equivalent　dose　rate　and　shielding　structure　weight.　As　a　result,　a　tradeoff　relationship　between　the　objectives　was　finally　obtained　in　the　form　of　a　Pareto　front.　The　optimization　results　revealed　significant　improvements　compared　with　the　current　RANS　shielding　configurations　in　terms　of　both　dose　and　weight.　The　results　indicate　that　a　reduction　in　shielding　weight　of　about　60%　can　be　obtained　by　adopting　the　optimized　shielding　structure　design,　without　sacrificing　shielding　performance.　The　performance　of　the　method　was　discussed　by　showing　advantages　of　NSGA-MC　over　the　so-called　weight　sum　method.　©　1963-2012　IEEE.