问题描述
我有一个 AbstractModel 和一个 ConcreteModel 来解决同样的问题，但它们的表现不同.主要是一个变量的初始值和ipopt的容忍度.
I have an AbstractModel and a ConcreteModel solving the same problem, but they are performing differently. It is mainly about initial value of a variable and tolerance of ipopt.
当我将变量 model.x 初始化为 10 并且 opt.options["tol"] = 1E-64 时:ConcreteModel 可以找到最优解，而抽象模型Solved To Acceptable Level".(但他们找到的解决方案其实是一样的)
When I initialize my variable model.x as 10 and opt.options["tol"] = 1E-64:ConcreteModel can find optimal solution, while abstract model "Solved To Acceptable Level". (But the solutions they find are actually the same)
当我将变量 model.x 初始化为 100 并且 opt.options["tol"] = 1E-64 时:ConcreteModel 可以找到最佳解决方案，而抽象模型有时会解决到可接受的水平"，有时无法加载状态不佳的 SolverResults 对象:错误".
When I initialize my variable model.x as 100 and opt.options["tol"] = 1E-64:ConcreteModel can find the optimal solution, while abstract model sometimes "Solved To Acceptable Level" and sometimes "Cannot load a SolverResults object with bad status: error".
如果我只是使用ipopt的默认容差值，无论我如何初始化变量model.x，ConcreteModel和AbstractModel都能找到相同的最优解.
If I just use the ipopt's default value of the tolerance, both ConcreteModel and AbstractModel can find the same optimal solution no matter how I initialize the variable model.x.
所以我想知道 opt.options["tol"] 有什么不同?为什么在这种情况下 ConcreteModel 总是能够找到最佳解决方案而 AbstractModel 不能?
So I wonder how opt.options["tol"] makes a difference? Why is ConcreteModel always able to find an optimal solution in this case while AbstractModel not?
变量
model.x = Var(model.Crops, model.Inputs, initialize = 100, within=NonNegativeReals)
AbstractModel 的求解脚本
solve script of AbstractModel
instance = model.create_instance(data="AbstractCDFarm.dat")
opt = SolverFactory("ipopt")
opt.options["tol"] = 1E-64
results = opt.solve(instance, tee=True)
instance.display()
ConcreteModel 求解脚本
solve script of ConcreteModel
opt = SolverFactory('ipopt')
opt.solve(model, tee=True)
opt.options["tol"] = 1E-64
results = opt.solve
model.display()
推荐答案
您为 ConcreteModel 调用了两次solve，看起来您看到的输出是针对默认 Ipopt 容差的，而不是针对 1E-64 容差的.你为什么设置这么低的容差?1E-64 比机器精度小，所以它是一个不可能收敛到的小公差.
You're calling solve twice for the ConcreteModel and it looks like the output you're seeing is for the default Ipopt tolerance not for the tolerance of 1E-64. Why are you setting such a low tolerance? 1E-64 is smaller than machine precision so it's an impossibly small tolerance to converge to.
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