如何在纸浆中安装不同的求解器？

Question

我有一个课程项目，要求我们使用松弛变量的价值以及问题中的成本降低。我已经提出并解决了问题，但是当我安装纸浆时，它仅下载并安装了一个求解器glpk_cmd。我认为该求解器正在使我的成本降低，而松弛值则显示为“无”，因为朋友可以运行它并用我的代码获得值。如何在纸浆中安装另一个求解器？我使用Anaconda安装Python，因此PIP对我不起作用。 '''

# Problem 1
from pulp import *
# Create LP
prob_1 = LpProblem("DoorProduction", LpMinimize)
solver.solver = getSolver('CPLEX_CMD')

#assign variables
M1 = LpVariable("Machine_1",0,350) #hours for machine 1
M2 = LpVariable("Machine_2",0,300) #hours for machine 2
O1 = LpVariable("Overtime_1",0) #overtime hours for machine 1
O2 = LpVariable("Overtime_2",0) #overtime hours for machine 2
S = LpVariable("Standard_Doors",25)
H = LpVariable("High_Security_Doors",25)
X = LpVariable("Max_Security_Doors",10)

# Objective Function
prob_1 += 30 * M1 + 40 * M2 + 65 * O1 + 90 * O2

# Constraints
prob_1 += 3 * S + 7 * H + 9 * X == M1 + O1, "Machine_One"
prob_1 += 4 * S + 5 * H + 7 * X == M2 + O2, "Machine_Two"
prob_1 += 540 * S + 760 * H + 950 * X >= 45000, "Revenue"

# Solve the problem
prob_1.solve(pulp.solvers.PULP_CBC_CMD(msg=True))
print("Status:", LpStatus[prob_1.status])

# Print results and variable values
for v in prob_1.variables():
    print(v.name, "=", v.varValue, "\trc =", v.dj)
print()

for name, c in prob_1.constraints.items():
    print(name, ":\t", c.pi, "\tslack =", c.slack)
print()

print("Optimal objective value", value(prob_1.objective))

revenue = 540 * S.varValue + 760 * H.varValue + 950 * X.varValue
profit = revenue - value(prob_1.objective)

print()
print("Revenue =",revenue)
print("Profit =", profit)

'''