blend_multi.py

from random import randint, uniform
def gen_data_content(m,n):
    # Oils down, acids accross (more oils than acids  m > n)
    R=[]
    for i in range(m):
        RR=[]
        P = 100
        for j in range(n-1):
            if P>1:
                acid = randint(1,min(70,P))*randint(0,1)
            else:
                acid = 0
            RR.append(acid)
            P -= acid
        RR.append(P)
        R.append(RR)
    return R
def gen_data_target(C):
    F=[]
    R0,R1=[],[]
    m,n=len(C),len(C[0])
    P=100
    R=[0 for j in range(n)]
    for i in range(m-1):
        if P:
            f=randint(1,min(20,P))
        else:
            f=0
        F.append(f)
        P-=f
        for j in range(n):
            acid = f*C[i][j]
            R[j] += acid
    f=P
    F.append(f)
    for j in range(n):
        acid = f*C[m-1][j]
        R[j] += acid
    for j in range(n):
        R0.append((0.95*R[j]/100.0))
        R1.append((1.05*R[j]/100.0))
    return [R0,R1]
def gen_data_cost(m,k):
    # Oils down, months accross
    R=[]
    for i in range(m):
        RR=[]
        for j in range(k):
            cost = randint(100,200)
            RR.append(cost)
        R.append(RR)
    return R
def gen_data_inventory(m):
    # Oils down
    R=[]
    for i in range(m):
        cost = [randint(0,200)]
        R.append(cost)
    return R

from my_or_tools import SolVal, ObjVal, newSolver

def solve_model(Part,Target,Cost,Inventory,D,SC,SL):
  s = newSolver('Multi-period soap blending problem')
  Oils= range(len(Part)) 
  Periods, Acids = range(len(Cost[0])), range(len(Part[0]))
  Buy = [[s.NumVar(0,D,'') for _ in Periods] for _ in Oils] 
  Blnd = [[s.NumVar(0,D,'') for _ in Periods] for _ in Oils] 
  Hold = [[s.NumVar(0,D,'') for _ in Periods] for _ in Oils] 
  Prod = [s.NumVar(0,D,'') for _ in Periods]            
  CostP= [s.NumVar(0,D*1000,'') for _ in Periods]  
  CostS= [s.NumVar(0,D*1000,'') for _ in Periods] 
  Acid = [[s.NumVar(0,D*D,'') for _ in Periods] for _ in Acids] 
  for i in Oils:                             
    s.Add(Hold[i][0] == Inventory[i][0])
  for j in Periods:                                      
    s.Add(Prod[j] == sum(Blnd[i][j] for i in Oils)) 
    s.Add(Prod[j] >= D)    
    if j < Periods[-1]:                                       
      for i in Oils:
        s.Add(Hold[i][j]+Buy[i][j]-Blnd[i][j] == Hold[i][j+1])
    s.Add(sum(Hold[i][j] for i in Oils) >= SL[0]) 
    s.Add(sum(Hold[i][j] for i in Oils) <= SL[1])
    for k in Acids: 
      s.Add(Acid[k][j]==sum(Blnd[i][j]*Part[i][k] for i in Oils))
      s.Add(Acid[k][j] >= Target[0][k] * Prod[j])
      s.Add(Acid[k][j] <= Target[1][k] * Prod[j])
    s.Add(CostP[j] == sum(Buy[i][j] * Cost[i][j] for i in Oils)) 
    s.Add(CostS[j] == sum(Hold[i][j] * SC for i in Oils))      
  Cost_product = s.Sum(CostP[j] for j in Periods)
  Cost_storage = s.Sum(CostS[j] for j in Periods)
  s.Minimize(Cost_product+Cost_storage)
  rc = s.Solve()
  B,L,H,A = SolVal(Buy),SolVal(Blnd),SolVal(Hold),SolVal(Acid)
  CP,CS,P = SolVal(CostP),SolVal(CostS),SolVal(Prod)
  return rc,ObjVal(s),B,L,H,P,A,CP,CS