"SEND+MORE=MONEY“任务的pyomo模型约束编程

from pyomo.environ import *

# 创建模型
model = ConcreteModel()

# 定义变量
model.S = Var(within=NonNegativeReals)
model.E = Var(within=NonNegativeReals)
model.N = Var(within=NonNegativeReals)
model.D = Var(within=NonNegativeReals)
model.M = Var(within=NonNegativeReals)
model.O = Var(within=NonNegativeReals)
model.R = Var(within=NonNegativeReals)
model.Y = Var(within=NonNegativeReals)

# 定义约束
model.constraints = ConstraintList()
model.constraints.add(S + E + N + D + M + O + R + E == 10*M + O + N + E + Y)
model.constraints.add(S >= 0)
model.constraints.add(S <= 9)
model.constraints.add(E >= 0)
model.constraints.add(E <= 9)
model.constraints.add(N >= 0)
model.constraints.add(N <= 9)
model.constraints.add(D >= 0)
model.constraints.add(D <= 9)
model.constraints.add(M >= 1)  # M不能为0
model.constraints.add(M <= 9)
model.constraints.add(O >= 0)
model.constraints.add(O <= 9)
model.constraints.add(R >= 0)
model.constraints.add(R <= 9)
model.constraints.add(Y >= 0)
model.constraints.add(Y <= 9)

# 定义目标函数（这里我们只需要找到满足约束的解）
model.objective = Objective(expr=1, sense=minimize)

# 求解模型
solver = SolverFactory('glpk')
results = solver.solve(model)

# 输出结果
if results.solver.termination_condition == TerminationCondition.optimal:
    print(f"S = {int(value(model.S))}")
    print(f"E = {int(value(model.E))}")
    print(f"N = {int(value(model.N))}")
    print(f"D = {int(value(model.D))}")
    print(f"M = {int(value(model.M))}")
    print(f"O = {int(value(model.O))}")
    print(f"R = {int(value(model.R))}")
    print(f"Y = {int(value(model.Y))}")
else:
    print("No solution found")