示例#1
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    def objective_rule(model):
        Workers_Cost = model.Ca * (model.alpha_put + model.alpha_pick) + \
                       model.Cb * sum((model.beta_put[t] + model.beta_pick[t])
                                       for t in model.TIMES)

        MHE_Cost = summation(model.MHE_cost)

        Tech_Cost = summation(model.Cth_put, model.theta_put) + \
                    summation(model.Cth_pick, model.theta_pick)


        Holding_Cost =  sum(model.C_hp[p] * model.y_pt[p,t]
                            for p in model.PRODUCTS for t in model.TIMES)
        Holding_Cost += sum(model.C_hq[q] * model.X_osq[s,q] * model.tau_sq[s,q]
                            for s in model.STORES for q in model.FASHION)
        Holding_Cost += sum(model.C_hsp[s,p] * model.y_spt[s,p,t]
                            for s in model.STORES for p in model.PRODUCTS for t in model.TIMES)
        Holding_Cost += sum(model.C_hsq[s,q] * model.y_sqt[s,q,t]
                            for s in model.STORES for q in model.FASHION for t in model.TIMES)


        Fixed_Shipping_Cost =  sum(model.C_fv[v] * model.n_vt[v,t]
                                  for v in model.VENDORS for t in model.TIMES)
        Fixed_Shipping_Cost += sum(model.C_fs[s] * model.n_st[s,t]
                                  for s in model.STORES for t in model.TIMES)


        Var_Shipping_Cost =  sum(model.C_vv[v] * model.W_p[p] * model.x_vpt[v,p,t]
                                  for v, p in model.OMEGA_P for t in model.TIMES)
        Var_Shipping_Cost += sum(model.C_vv[v] * model.W_q[q] * model.X_ivq[v,q] * model.rho_vqt[v,q,t]
                                  for v, q in model.OMEGA_Q for t in model.TIMES)
        Var_Shipping_Cost += sum(model.C_vs[s] * model.W_p[p] * model.x_spt[s,p,t]
                                  for s in model.STORES for p in model.PRODUCTS for t in model.TIMES)
        Var_Shipping_Cost += sum(model.C_vs[s] * model.W_q[q] * model.X_osq[s,q] * model.rho_sqt[s,q,t]
                                  for s in model.STORES for q in model.FASHION for t in model.TIMES)


        FS_Expr = (Workers_Cost + MHE_Cost + Tech_Cost + Holding_Cost
                                + Fixed_Shipping_Cost + Var_Shipping_Cost)

        return FS_Expr
示例#2
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def objective(model):
    """Abstract representation of our model objective.""" 
    obj = pyomo.summation(model.c, model.x)
    return obj
示例#3
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文件: urbs.py 项目: Simon0241/urbs
 def obj_rule(m):
     return pyomo.summation(m.costs)
示例#4
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文件: urbs.py 项目: Simon0241/urbs
 def res_co2_emission_rule(m):
     return (pyomo.summation(m.co2_pro_out) * m.weight <=
             m.commodity.loc['Global', 'CO2', 'Env']['max'])
示例#5
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def obj_rule(m):
    return pyomo.summation(m.flow)  # == short for sum{a1,a2} flow[a1,a2]
示例#6
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文件: vicus.py 项目: kamilien1/vicus
 def res_co2_emission_rule(m):
     return pyomo.summation(m.co2_pro_out) <= \
            m.commodity.loc['CO2','Env']['max']
示例#7
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文件: vicus.py 项目: kamilien1/vicus
 def obj_rule(m):
     """ Return sum of total costs over all cost types.
     
     Simply calculates the sum of m.costs over all m.cost_types.
     """
     return pyomo.summation(m.costs)
示例#8
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def constraint4_rule(model):
    expr = model.gamma * model.A_put - \
          summation(model.Lambda_put, model.zeta_put)
    return (None, expr, 0)
示例#9
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def constraint7_rule(model):
    expr = model.gamma * model.A_pick - \
          summation(model.Lambda_pick, model.zeta_pick)
    return (None, expr, 0)
示例#10
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def constraint2_rule(model):
    return (summation(model.theta_pick), 1)
示例#11
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def constraint1_rule(model):
    return (summation(model.theta_put), 1)
示例#12
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def objectiveB_rule(model):
    expr = model.Ca * (model.alpha_put + model.alpha_pick) + \
          summation(model.Cth_put, model.theta_put) + \
          summation(model.Cth_pick, model.theta_pick)
    return (expr, model.FirstStageCost)
示例#13
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 def obj_rule(m):
     """ Return sum of total costs over all cost types.
     
     Simply calculates the sum of m.costs over all m.cost_types.
     """
     return pyomo.summation(m.costs)
示例#14
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 def res_co2_emission_rule(m):
     return pyomo.summation(m.co2_pro_out) <= \
            m.commodity.loc['CO2','Env']['max']