Through　the　control　of　excessive　daylight　in　buildings,　shading　devices　can　reduce　glare　and　improve　occupants???　visual　comfort.　However,　shading　devices　may　overly　reduce　illuminance　levels.　Many　shading　strategies　are　available,　but　they　do　not　perform　equally　well,　and　tradi-tionally,　it　has　been　difficult　to　select　the　most　suitable　shading　strategy.　This　study　proposed　a　parameterization　method　for　the　selection　and　design　of　a　shading　strategy　that　would　reduce　glare　while　maintaining　a　satisfactory　daylighting　level,　through　the　construction　of　Pareto　sets　based　on　a　multi-objective　genetic　algorithm.　The　objective　function　was　created　by　combining　a　dynamic　glare　evaluation　indicator,　the　spatial　glare　autonomy　(sGA),　and　a　self-constructed　daylight　index,　the　spatial　daylight　vote　autonomy　(sDVA),　developed　from　a　field　survey.　As　a　case　study,　the　proposed　method　was　used　to　compare　the　performance　of　four　shading　strategies,　including　vertical　slats　(Vs),　a　perforated　aluminum　sheet　(PAS),　serrated　windows　with　southern　orientation　(Sw_S),　and　serrated　windows　with　northern　orientation　(Sw_N)　in　a　university　library　in　Shanghai,　China.　It　was　found　that　the　Sw_S　and　PAS　had　a　relatively　bad　performance;　the　Vs　performed　better　than　the　Sw_N　in　providing　a　more　satisfactory　illuminance　level;　and　the　Sw_N　was　more　effective　in　reducing　the　glare.　The　multi-objective　optimization　process　can　be　used　to　obtain　near-optimal　design　parameters　that　create　a　visual　environment　with　reduced　glare　while　maintaining　an　acceptable　illuminance　level,　for　all　four　shading　strategies.　The　developed　method　can　be　a　helpful　tool　in　the　design　of　an　appropriate　daylighting　environment.