采用Gurobi+Python平台，非线性规划计算
Gurobi+Python平台、Python+Gurobi入门代码参考：from gurobipy import *
def HFS_Model_MS(nJ, M, P):
print('MS')
# model
m = Model()
X = {}
Y = {}
T = {}
C = {}
CS = {}
S = {}
bigM = {}
ms = {}
# paramters
Mi = [[], [], [], []]
nI = len(M)
nL = len(P)
bigM = 100000
it = 0
for i in range(nI):
for j in range(M):
Mi.append(it)
it = it + 1
# variables
for j in range(nJ):
for k in range(nJ):
X[(j, k)] = m.addVar(vtype=GRB.BINARY, name="X%d,%d" % (j, k))
for i in range(nI):
for k in range(nJ):
for l in range(nL):
Y[(i, k, l)] = m.addVar(vtype=GRB.BINARY, name="Y%d,%d,%d" % (i, k, l))
for j in range(nJ):
for i in range(nI):
T[(j, i)] = m.addVar(vtype=GRB.CONTINUOUS, name="T%d,%d" % (j, i))
C[(j, i)] = m.addVar(vtype=GRB.CONTINUOUS, name="C%d,%d" % (j, i))
for i in range(nI):
for k in range(nJ):
CS[(i, k)] = m.addVar(vtype=GRB.CONTINUOUS, name="CS%d,%d" % (i, k))
S[(i, k)] = m.addVar(vtype=GRB.CONTINUOUS, name="S%d,%d" % (i, k))
ms = m.addVar(vtype=GRB.CONTINUOUS, name='ms')
m.update()
# constraints
for j in range(nJ):
m.addConstr(quicksum(X[(j, k)] for k in range(nJ)) == 1)
for k in range(nJ):
m.addConstr(quicksum(X[(j, k)] for j in range(nJ)) == 1)
for i in range(nI):
for k in range(nJ):
m.addConstr(quicksum(Y[(i, k, l)] for l in Mi) == 1)
for i in range(nI - 1):
for j in range(nJ):
for k in range(nJ):
for l in range(nL):
m.addConstr(T[(j, i + 1)] >= T[(j, i)] + P - bigM * (2 - X[(j, k)] - Y[(i, k, l)]))
for i in range(nI):
for k in range(1, nJ):
for t in range(nJ):
for l in range(nL):
if (t < k):
m.addConstr(S[(i, k)] >= S[(i, t)] + quicksum(
P * X[(j, t)] - bigM * (2 - Y[(i, k, l)] - Y[(i, t, l)]) for j in range(nJ)))
for i in range(nI):
for k in range(nJ):
for j in range(nJ):
m.addConstr(S[(i, k)] >= T[(j, i)] - bigM * (1 - X[(j, k)]))
m.addConstr(S[(i, k)] <= T[(j, i)] + bigM * (1 - X[(j, k)]))
for i in range(nI):
for j in range(nJ):
for k in range(nJ):
for l in range(nL):
m.addConstr(C[(j, i)] >= T[(j, i)] + P - bigM * (2 - X[(j, k)] - Y[(i, k, l)]))
for i in range(nI):
for k in range(nJ):
for l in range(nL):
m.addConstr(CS[(i, k)] >= S[(i, k)] + quicksum(X[(j, k)] * P for j in range(nJ)) - bigM * (
1 - Y[(i, k, l)]))
for i in range(nI):
for j in range(nJ):
m.addConstr(T[(j, i)] >= 0)
m.addConstr(C[(j, i)] >= 0)
for i in range(nI):
for k in range(nJ):
m.addConstr(S[(i, k)] >= 0)
m.addConstr(CS[(i, k)] >= 0)
for j in range(nJ):
m.addConstr(ms >= C[(j, nI - 1)])
# set objective
m.setObjective(ms, GRB.MINIMIZE)
m.setParam("TimeLimit", 3600)
m.setParam("OutputFlag", False)
# optimize
m.optimize()
# for (j, k) in X:
# if X[(j, k)].x >= 0.9:
# print("Wert von X" + str((j, k)) + ": " + str(X[(j, k)].x))
# for (i, k, l) in Y:
# if Y[(i, k, l)].x >= 0.9:
# print("Wert von Y" + str((i, k, l)) + ": " + str(Y[(i, k, l)].x))
# for (j,i) in T:
# if T[(j,i)].x >= 1:
# print("Wert von T" + str((j,i))+ ": " + str(T[(j,i)].x ))
# for (i,k) in S:
# if S[(i,k)].x >= 1:
# print("Wert von S" + str((i,k))+ ": " + str(S[(i,k)].x ))
# for (j, i) in C:
# if C[(j,i)].x >= 1:
#print("Wert von C" + str((j, i)) + ": " + str(C[(j, i)].x))
# for (i,k) in CS:
# if CS[(i,k)].x >= 1:
# print("Wert von CS" + str((i,k))+ ": " + str(CS[(i,k)].x ))
m.write("model_ms.lp")
return m.objVal, m.Runtime, m.status
def main():
nJ = 0
M =
P = []
results_MS = open("Results_MS.txt", "w")
results_MS.write("Nr." + "" + "Obj_Val" + "" + "Run_Time" + "" + "Status \n")
for inst in range(13,192):
with open("I4_" + str(inst + 1) + ".txt", "r") as textFile:
lines =
textFile.close()
nJ = int(lines)
M = int(lines)
M = int(lines)
M = int(lines)
M = int(lines)
nM: int = M + M + M + M
P = [ for j in range(nJ)]
z = 0
for i in range(nM):
for j in range(nJ):
P = float(lines)
z = z + 1
print(inst)
obj_Val_MS, run_Time_MS, status_MS = HFS_Model_MS(nJ, M, P)
results_MS.write(
str(inst + 1) + "" + str(obj_Val_MS) + "" + str(run_Time_MS) + "" + str(status_MS) + "\n")
results_MS.close()
main()
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