Hi,
if you name your constraints
subject to {
forall(i in N)
ct1:sum(j in N:j!=i,k in Trucks)(x[i][j][k])==1;
forall(j in N)
ct2:sum(i in N:i!=j,k in Trucks)(x[i][j][k])==1;
forall(k in Trucks)
ct3:sum(j in N)(x[1][j][k])==1;
forall(k in Trucks)
ct4:sum(i in N)(x[i][1][k])==1;
forall(h in A,k in Trucks)
ct5:sum(i in A:i!=h)(x[i][h][k])-sum(j in A)(x[h][j][k])==0;//Õâ¸öÒª°üº¬Æðµã
forall(k in Trucks)
ct6:sum(i,j in A:j!=i)(c[i][j][k]*x[i][j][k]+t[j][k]*x[i][j][k])<=T;
forall(i,j in A:j!=i,k in Trucks)
ct7:q[j][k]>=q[i][k]-d[i]-Z*(1-x[i][j][k]);//ÕâÀïÓ¦¸ÃÓÐÎÊÌâ
forall(i in A,k in Trucks)
ct8:maxl(0,d[i])<=q[i][k];
forall(i in A,k in Trucks)
ct9:q[i][k]<=Q[k];
forall(i,j in A:j!=i,k in Trucks)
ct10:v[j][k] >= v[i][k] -m[i]-Z*(1-x[i][j][k]);
forall(i in A,k in Trucks)
maxl(0,m[i])<=v[i][k];
forall(i in A,k in Trucks)
ct11:v[i][k]<=V[k];
forall(i,j in A:j!=i,k in Trucks)
ct12:w[j][k] >= w[i][k]+t[j][k]+c[i][j][k]-Z*(1-x[i][j][k]);
forall(i in A,k in Trucks)
ct13:a[i]<=sum(k in Trucks)w[i][k];
forall(i in A,k in Trucks)
sum(k in Trucks)w[i][k]<=b[i];
}
then you ll get some conflicts and relaxations that will help you find why your model is not feasible.
regards
https://www.linkedin.com/pulse/%E4%BC%98%E5%8C%96%E5%B0%91%E8%8A%B1%E9%92%B1%E5%A4%9A%E5%8A%9E%E4%BA%8B-%E5%8A%A8%E7%89%A9%E5%9B%AD%E5%85%AC%E5%85%B1%E6%B1%BD%E8%BD%A6%E5%92%8C%E5%84%BF%E7%AB%A5-alex-fleischer/
#DecisionOptimization#OPLusingCPLEXOptimizer