如何解决如何在python中使用Gurobi的MIPGap和TimeLimit?
我正在大规模进行MILP。因此,我必须将时间限制设置为合理的值,或者将MIPGap设置为合理的水平。我已经知道gurobi的文档。
MIPGap:https://www.gurobi.com/documentation/6.5/refman/mipgap.html
TimeLimit:https://www.gurobi.com/documentation/8.0/refman/timelimit.html#parameter:TimeLimit
当找到最佳百分比的解决方案时,MIPGap Gurobi将停止
TimeLimit Gurobi将在一定时间后停止。
但是您能给我一个例子,将时间限制设置为5分钟吗? 或将MIPGap设置为5%?
我不知道该如何准确地实现那些角色?
请帮助我,我对python还是很陌生
我尝试了这个,但这不起作用
model.Params.TimeLimit = 5
model.setParam("MIPGap",mipgap)
这是我模型的简短版本
from gurobipy import *
import csv
import geopandas as gpd
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from pandas.core.common import flatten
import math
################################# SOLVE function START ###################################################################
def solve(
vpmaint,wpunit,wuunit,vumaint,kfuel,koil,kbio,hb,ht,cj,ci,zinvestp,zinvestu,DEMAND,DEMANDM,LOCATION,SOURCE,BTYPE,SOURCEM,osi,oij,ojm
):
model = Model("Biomass to liquid supply chain network design")
################################# SOLVE function END ###################################################################
####################################################### variable section START ####################################################################################################
#binary variables ############################# Binary 1-2 ####################################################
#binary 1: Pyrolyse i with capacity p open?
fpopen = {}
for i in LOCATION:
for p in R:
fpopen[i,p] = model.addVar(vtype = GRB.BINARY,name = "fpopen_%s_%s" % (i,p))
#binary 2: Upgrading j with capacity r and technology t open?
fuopen = {}
for j in LOCATION:
for r in R:
for t in TECHNOLOGY:
fuopen[j,r,t] = model.addVar(vtype = GRB.BINARY,name = "fuopen_%s_%s_%s" % (j,t))
################################################ continous variables Integer 1-9 #############################################################
#integer 1: Mass of Biomass type b from Source s to Pyrolyse i
xsi = {}
for s in SOURCE:
for i in LOCATION:
for b in BTYPE:
xsi[s,i,b] = model.addVar(vtype = GRB.INTEGER,name = "xsi_%s_%s_%s" % (s,b))
#integer 2:Mass of Biomass type b from Source s to Pyrolyse i
xjm = {}
for j in LOCATION:
for m in DEMAND:
xjm[j,m] = model.addVar(vtype = GRB.INTEGER,name = "xjm_%s_%s" % (j,m))
model.update()
model.modelSense = GRB.MAXIMIZE
####################################################### Objective Function START
model.setobjective(
#quicksum(DEMANDM[m] * l for m in DEMANDM )
quicksum(xjm[j,m] * l for j in LOCATION for m in DEMAND)
- quicksum(ainvest[i] + aoperation[i] + aprod[i] for i in LOCATION)
- quicksum(einvest[j] + eoperation[j] + eprod[j] for j in LOCATION)
## ......
####################################################### Constraints
############################## Satisfy Demand Constraint 1-3
# Constraint 1: Always Satisfy Demand at marketplace m
for m in DEMAND:
model.addConstr(quicksum(xjm[j,m] for j in LOCATION) <= int(DEMANDM[m]))
# for m in DEMAND:
# model.addConstr(quicksum(x[j,m] for j in LOCATION) >= DEMANDM[m])
# Constraint 2: The amount of bio-oil sent from pyrolyse station i to Upgrading
###...Here are more constraints
model.optimize()
model.getvars()
model.MIPGap = 5
model.Params.TimeLimit = 1.0
model.setParam("MIPGap",mipgap)
解决方法
在调用Model.optimize()之前,需要设置参数。同样,MIPGap和TimeLimit的单位分别是小数和秒。因此您的代码应为:
model.Params.MIPGap = 0.05 # 5%
model.Params.TimeLimit = 300 # 5 minutes
model.optimize()
,
或者,您可以调用模型的setParam()
method:
model.setParam('MIPGap',0.05)
model.setParam('Timelimit',300)
,
我已经有两年没有运行这段代码了……我再也没有Gurobi许可证了。但是,这样的事情应该起作用。您没有提到如何编码模型。以下来自pyomo
脚本。我认为类似的方法也可以,但是您可以在求解器实例上找到一个句柄。
solver = SolverFactory("gurobi")
solver.options['timeLimit'] = 1200 # seconds
solver.options['mipgap'] = 0.01
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