本文整理汇总了Python中pyomo.environ.ConcreteModel.specs1方法的典型用法代码示例。如果您正苦于以下问题:Python ConcreteModel.specs1方法的具体用法?Python ConcreteModel.specs1怎么用?Python ConcreteModel.specs1使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyomo.environ.ConcreteModel
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在下文中一共展示了ConcreteModel.specs1方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: build_eight_process_flowsheet
# 需要导入模块: from pyomo.environ import ConcreteModel [as 别名]
# 或者: from pyomo.environ.ConcreteModel import specs1 [as 别名]
#.........这里部分代码省略.........
m.use_unit4 = Disjunct()
m.use_unit4.inout4 = Constraint(
expr=1.25 * (m.flow[12] + m.flow[14]) == m.flow[13])
m.use_unit4.no_unit5_flow = Constraint(expr=m.flow[15] == 0)
m.use_unit5 = Disjunct()
m.use_unit5.inout5 = Constraint(expr=m.flow[15] == 2 * m.flow[16])
m.use_unit5.no_unit4_flow1 = Constraint(expr=m.flow[12] == 0)
m.use_unit5.no_unit4_flow2 = Constraint(expr=m.flow[14] == 0)
m.no_unit4or5 = Disjunct()
m.no_unit4or5.no_unit5_flow = Constraint(expr=m.flow[15] == 0)
m.no_unit4or5.no_unit4_flow1 = Constraint(expr=m.flow[12] == 0)
m.no_unit4or5.no_unit4_flow2 = Constraint(expr=m.flow[14] == 0)
m.use_unit6 = Disjunct()
m.use_unit6.inout6 = Constraint(
expr=exp(m.flow[20] / 1.5) - 1 == m.flow[19])
m.use_unit6.no_unit7_flow1 = Constraint(expr=m.flow[21] == 0)
m.use_unit6.no_unit7_flow2 = Constraint(expr=m.flow[22] == 0)
m.use_unit7 = Disjunct()
m.use_unit7.inout7 = Constraint(expr=exp(m.flow[22]) - 1 == m.flow[21])
m.use_unit7.no_unit6_flow1 = Constraint(expr=m.flow[19] == 0)
m.use_unit7.no_unit6_flow2 = Constraint(expr=m.flow[20] == 0)
m.no_unit6or7 = Disjunct()
m.no_unit6or7.no_unit7_flow1 = Constraint(expr=m.flow[21] == 0)
m.no_unit6or7.no_unit7_flow2 = Constraint(expr=m.flow[22] == 0)
m.no_unit6or7.no_unit6_flow = Constraint(expr=m.flow[19] == 0)
m.no_unit6or7.no_unit6_flow2 = Constraint(expr=m.flow[20] == 0)
m.use_unit8 = Disjunct()
m.use_unit8.inout8 = Constraint(
expr=exp(m.flow[18]) - 1 == m.flow[10] + m.flow[17])
m.no_unit8 = Disjunct()
m.no_unit8.no_unit8_flow1 = Constraint(expr=m.flow[10] == 0)
m.no_unit8.no_unit8_flow2 = Constraint(expr=m.flow[17] == 0)
m.no_unit8.no_unit8_flow3 = Constraint(expr=m.flow[18] == 0)
# Mass balance equations
m.massbal1 = Constraint(expr=m.flow[13] == m.flow[19] + m.flow[21])
m.massbal2 = Constraint(
expr=m.flow[17] == m.flow[9] + m.flow[16] + m.flow[25])
m.massbal3 = Constraint(expr=m.flow[11] == m.flow[12] + m.flow[15])
m.massbal4 = Constraint(
expr=m.flow[3] + m.flow[5] == m.flow[6] + m.flow[11])
m.massbal5 = Constraint(expr=m.flow[6] == m.flow[7] + m.flow[8])
m.massbal6 = Constraint(expr=m.flow[23] == m.flow[20] + m.flow[22])
m.massbal7 = Constraint(expr=m.flow[23] == m.flow[14] + m.flow[24])
# process specifications
m.specs1 = Constraint(expr=m.flow[10] <= 0.8 * m.flow[17])
m.specs2 = Constraint(expr=m.flow[10] >= 0.4 * m.flow[17])
m.specs3 = Constraint(expr=m.flow[12] <= 5 * m.flow[14])
m.specs4 = Constraint(expr=m.flow[12] >= 2 * m.flow[14])
# pure integer constraints
m.use1or2 = Disjunction(expr=[m.use_unit1, m.use_unit2])
m.use4or5maybe = Disjunction(
expr=[m.use_unit4, m.use_unit5, m.no_unit4or5])
m.use4or5 = Constraint(
expr=m.use_unit4.indicator_var + m.use_unit5.indicator_var <= 1)
m.use6or7maybe = Disjunction(
expr=[m.use_unit6, m.use_unit7, m.no_unit6or7])
m.use4implies6or7 = Constraint(
expr=m.use_unit6.indicator_var + m.use_unit7.indicator_var -
m.use_unit4.indicator_var == 0)
m.use3maybe = Disjunction(expr=[m.use_unit3, m.no_unit3])
m.either3ornot = Constraint(
expr=m.use_unit3.indicator_var + m.no_unit3.indicator_var == 1)
m.use8maybe = Disjunction(expr=[m.use_unit8, m.no_unit8])
m.use3implies8 = Constraint(
expr=m.use_unit3.indicator_var - m.use_unit8.indicator_var <= 0)
"""Profit (objective) function definition"""
m.profit = Objective(expr=sum(
getattr(m, 'use_unit%s' % (unit,)).indicator_var * CF[unit]
for unit in m.units) +
sum(m.flow[stream] * CV[stream]
for stream in m.streams) + CONSTANT,
sense=minimize)
"""Bound definitions"""
# x (flow) upper bounds
x_ubs = {3: 2, 5: 2, 9: 2, 10: 1, 14: 1, 17: 2, 19: 2, 21: 2, 25: 3}
for i, x_ub in iteritems(x_ubs):
m.flow[i].setub(x_ub)
# # optimal solution
# m.use_unit1.indicator_var = 0
# m.use_unit2.indicator_var = 1
# m.use_unit3.indicator_var = 0
# m.no_unit3.indicator_var = 1
# m.use_unit4.indicator_var = 1
# m.use_unit5.indicator_var = 0
# m.no_unit4or5.indicator_var = 0
# m.use_unit6.indicator_var = 1
# m.use_unit7.indicator_var = 0
# m.no_unit6or7.indicator_var = 0
# m.use_unit8.indicator_var = 1
# m.no_unit8.indicator_var = 0
return m
示例2: build_eight_process_flowsheet
# 需要导入模块: from pyomo.environ import ConcreteModel [as 别名]
# 或者: from pyomo.environ.ConcreteModel import specs1 [as 别名]
#.........这里部分代码省略.........
m.flow[2] == 0,
m.flow[3] == 0]
])
m.use_unit_3ornot = Disjunction(
expr=[
# Use unit 3 disjunct
[m.yCF[3] == m.CF[3],
1.5 * m.flow[9] + m.flow[10] == m.flow[8]],
# No unit 3 disjunct
[m.flow[9] == 0,
m.flow[10] == m.flow[8]]
])
m.use_unit_4or5ornot = Disjunction(
expr=[
# Use unit 4 disjunct
[m.yCF[4] == m.CF[4],
1.25 * (m.flow[12] + m.flow[14]) == m.flow[13],
m.flow[15] == 0],
# Use unit 5 disjunct
[m.yCF[5] == m.CF[5],
m.flow[15] == 2 * m.flow[16],
m.flow[12] == 0,
m.flow[14] == 0],
# No unit 4 or 5 disjunct
[m.flow[15] == 0,
m.flow[12] == 0,
m.flow[14] == 0]
])
m.use_unit_6or7ornot = Disjunction(
expr=[
# use unit 6 disjunct
[m.yCF[6] == m.CF[6],
exp(m.flow[20] / 1.5) - 1 == m.flow[19],
m.flow[21] == 0,
m.flow[22] == 0],
# use unit 7 disjunct
[m.yCF[7] == m.CF[7],
exp(m.flow[22]) - 1 == m.flow[21],
m.flow[19] == 0,
m.flow[20] == 0],
# No unit 6 or 7 disjunct
[m.flow[21] == 0,
m.flow[22] == 0,
m.flow[19] == 0,
m.flow[20] == 0]
])
m.use_unit_8ornot = Disjunction(
expr=[
# use unit 8 disjunct
[m.yCF[8] == m.CF[8],
exp(m.flow[18]) - 1 == m.flow[10] + m.flow[17]],
# no unit 8 disjunct
[m.flow[10] == 0,
m.flow[17] == 0,
m.flow[18] == 0]
])
# Mass balance equations
m.massbal1 = Constraint(expr=m.flow[13] == m.flow[19] + m.flow[21])
m.massbal2 = Constraint(
expr=m.flow[17] == m.flow[9] + m.flow[16] + m.flow[25])
m.massbal3 = Constraint(expr=m.flow[11] == m.flow[12] + m.flow[15])
m.massbal4 = Constraint(
expr=m.flow[3] + m.flow[5] == m.flow[6] + m.flow[11])
m.massbal5 = Constraint(expr=m.flow[6] == m.flow[7] + m.flow[8])
m.massbal6 = Constraint(expr=m.flow[23] == m.flow[20] + m.flow[22])
m.massbal7 = Constraint(expr=m.flow[23] == m.flow[14] + m.flow[24])
# process specifications
m.specs1 = Constraint(expr=m.flow[10] <= 0.8 * m.flow[17])
m.specs2 = Constraint(expr=m.flow[10] >= 0.4 * m.flow[17])
m.specs3 = Constraint(expr=m.flow[12] <= 5 * m.flow[14])
m.specs4 = Constraint(expr=m.flow[12] >= 2 * m.flow[14])
# pure integer constraints
m.use4implies6or7 = Constraint(
expr=m.use_unit_6or7ornot.disjuncts[0].indicator_var +
m.use_unit_6or7ornot.disjuncts[1].indicator_var -
m.use_unit_4or5ornot.disjuncts[0].indicator_var == 0)
m.use3implies8 = Constraint(
expr=m.use_unit_3ornot.disjuncts[0].indicator_var
- m.use_unit_8ornot.disjuncts[0].indicator_var <= 0)
"""Profit (objective) function definition"""
m.profit = Objective(expr=sum(
m.yCF[unit]
for unit in m.units) +
sum(m.flow[stream] * CV[stream]
for stream in m.streams) + CONSTANT,
sense=minimize)
"""Bound definitions"""
# x (flow) upper bounds
x_ubs = {3: 2, 5: 2, 9: 2, 10: 1, 14: 1, 17: 2, 19: 2, 21: 2, 25: 3}
for i, x_ub in iteritems(x_ubs):
m.flow[i].setub(x_ub)
# Optimal solution uses units 2, 4, 6, 8 with objective value 68.
return m