Gurobi Model Infeasible or unbounded

Hi all,

I am solving a model consisting of several periods of reward, when I solve the model for one period (T = 1), I can get the result. But once I specify it to 2 periods (T = 2), it is not solvable. The math shouldn't be difficult since the two-period problem is the summation of two single-period problems. 

I am struggling with this problem for a long time, then I simplified the original problem just to find what went wrong first. Please find the attached code. Thank you so much for your help! - Ye

import gurobipy as gp

from gurobipy import GRB, abs_
T = 2
try:
    m_ML2 = gp.Model("Model")    
    # define decision variables   
    x1_1 = m_ML2.addVars(T, name = 'x1_1', lb = 0)
    x2_1 = m_ML2.addVars(T, name = 'x2_1', lb = 0)
    y1_1 = m_ML2.addVars(T, name = 'y1_1', lb = 0)
    y2_1 = m_ML2.addVars(T, name = 'y2_1', lb = 0)
        
    s1_1 = m_ML2.addVars(T, name = 's1_1', lb = 0)
    s2_1 = m_ML2.addVars(T, name = 's2_1', lb = 0)
    s1_11 = m_ML2.addVar(vtype = GRB.CONTINUOUS, name = 's1_11', lb = 0)  
    s2_11 = m_ML2.addVar(vtype = GRB.CONTINUOUS, name = 's2_11', lb = 0)  
          
    R1 = m_ML2.addVars(T, name = 'R1')
    
    for i in range(T):
            s1_1[i] = w1[i]
            s2_1[i] = w2[i] 
                
            m_ML2.addConstr(s1_11 == s1_1[i])
            m_ML2.addConstr(s2_11 == s2_1[i])
            #set value for decision variable
            m_ML2.addConstr(y2_1[i] == 0)
            m_ML2.addConstr(x2_1[i] == s2_11)
            
            m_ML2.addConstr(y1_1[i] == 0 )
            m_ML2.addConstr(x1_1[i] == s1_11)
            #reward
            m_ML2.addConstr(R1[i] == P[0,i]*(y2_1[i]+(1-alpha)*y1_1[i])+P[1,i]*x2_1[i]+P[2,i]*x1_1[i]-P[4,i]*(q-y1_1[i]-y2_1[i])-P[3,i]*(w1[i]+w2[i]))

       
    m_ML2.setObjective(R1.sum(), GRB.MAXIMIZE)         
    # Optimize model
    m_ML2.optimize()
    
    
    for v in m_ML2.getVars():
        print('%s %g' % (v.varName, v.x))

    print('Obj: %g' % m_ML2.objVal)

except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ': ' + str(e))

except AttributeError:
    print('Encountered an attribute error')