写一段lingo的多目标优化代码

以下是一段使用Lingo语言实现多目标优化的示例代码：

model multi_obj_optimization
  ! Objective functions to be minimized
  minimize f1 = x1^2 + x2^2
  minimize f2 = (x1-2)^2 + (x2-1)^2
  ! Decision variables
  decision variables
    x1 >= 0
    x1 <= 5
    x2 >= 0
    x2 <= 5
  end
  ! Constraints
  subject to
    constraint1: x1 - 2*x2 + 1 >= 0
    constraint2: -x1 - 2*x2 + 4 >= 0
  end
end

! Set up the optimization problem
set model = multi_obj_optimization
let nobjs = 2 ! Number of objectives
let nvars = 2 ! Number of decision variables

! Set up the optimizer
let optimizer = LINDO_GLOBAL
set optimizer.algorithm = 9 ! Use NSGA-II algorithm
set optimizer.nsga2.popsize = 100 ! Set population size
set optimizer.nsga2.maxgen = 50 ! Set maximum number of generations

! Solve the optimization problem
optimize(model)

! Print the results
print "Optimal objective values:"
for i = 1 to nobjs do
  print "f" & i & " = " & getobj(model, i)
end for
print "Optimal decision variables:"
for j = 1 to nvars do
  print "x" & j & " = " & getsol(model, j)
end for

该代码中，我们定义了两个需要最小化的目标函数 `f1` 和 `f2`，并将它们作为模型的一部分。我们还定义了两个决策变量 `x1` 和 `x2`，以及两个约束条件 `constraint1` 和 `constraint2`。我们使用 LINDO_GLOBAL 优化器，并将其设置为使用 NSGA-II 算法进行多目标优化。最后，我们打印出了最优目标函数值和最优决策变量值。