I am trying to estimate a mixed logit model to understand taste variation among the people. In my sample, there are 5000 people as decision makers and each of them make repeated choices ranging from 1 to 300 times. So I end up having 160000 observations.

I tried to use PROC MDC first (code listed below), then this model takes 160000 observation at one time and I can't specify individual person as cluster.  
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  proc mdc data=gdp.matlab_model_0610 type=mixedlogit;
      model response =
ini_dly_beta_trun
dly_sav_min2
freq
distance
rev
hub
mj_index
prm_airlines
marketfare
seat
/
               nchoice=2
               mixed=(normalparm=ini_dly_beta_trun  dly_sav_min2);
      id id;
   run;
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Then I tried PROC GLIMMIX, then it can't converge. Damn it....
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proc glimmix INITGLM data=gdp.y7;
class cluster;
model response  =
ini_dly_beta_trun
dly_sav_min2
freq
distance
rev
hub
mj_index
prm_airlines
marketfare
seat  /   
dist=binary     link=logit
solution ;
random ini_dly_beta_trun
dly_sav_min2
/subject=cluster ;
;
run;
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