本文整理汇总了Python中pyscipopt.Model.relax方法的典型用法代码示例。如果您正苦于以下问题：Python Model.relax方法的具体用法？Python Model.relax怎么用？Python Model.relax使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyscipopt.Model的用法示例。
在下文中一共展示了Model.relax方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: solveCuttingStock
# 需要导入模块: from pyscipopt import Model [as 别名]
# 或者: from pyscipopt.Model import relax [as 别名]
def solveCuttingStock(w,q,B):
"""solveCuttingStock: use column generation (Gilmore-Gomory approach).
Parameters:
- w: list of item's widths
- q: number of items of a width
- B: bin/roll capacity
Returns a solution: list of lists, each of which with the cuts of a roll.
"""
t = [] # patterns
m = len(w)
# Generate initial patterns with one size for each item width
for (i,width) in enumerate(w):
pat = [0]*m # vector of number of orders to be packed into one roll (bin)
pat[i] = int(B/width)
t.append(pat)
# if LOG:
# print "sizes of orders=",w
# print "quantities of orders=",q
# print "roll size=",B
# print "initial patterns",t
K = len(t)
master = Model("master LP") # master LP problem
x = {}
for k in range(K):
x[k] = master.addVar(vtype="I", name="x(%s)"%k)
orders = {}
for i in range(m):
orders[i] = master.addCons(
quicksum(t[k][i]*x[k] for k in range(K) if t[k][i] > 0) >= q[i], "Order(%s)"%i)
master.setObjective(quicksum(x[k] for k in range(K)), "minimize")
# master.Params.OutputFlag = 0 # silent mode
# iter = 0
while True:
# print "current patterns:"
# for ti in t:
# print ti
# print
# iter += 1
relax = master.relax()
relax.optimize()
pi = [relax.getDualsolLinear(c) for c in relax.getConss()] # keep dual variables
knapsack = Model("KP") # knapsack sub-problem
knapsack.setMaximize # maximize
y = {}
for i in range(m):
y[i] = knapsack.addVar(lb=0, ub=q[i], vtype="I", name="y(%s)"%i)
knapsack.addCons(quicksum(w[i]*y[i] for i in range(m)) <= B, "Width")
knapsack.setObjective(quicksum(pi[i]*y[i] for i in range(m)), "maximize")
knapsack.hideOutput() # silent mode
knapsack.optimize()
# if LOG:
# print "objective of knapsack problem:", knapsack.ObjVal
if knapsack.getObjVal() < 1+EPS: # break if no more columns
break
pat = [int(y[i].X+0.5) for i in y] # new pattern
t.append(pat)
# if LOG:
# print "shadow prices and new pattern:"
# for (i,d) in enumerate(pi):
# print "\t%5s%12s%7s" % (i,d,pat[i])
# print
# add new column to the master problem
col = Column()
for i in range(m):
if t[K][i] > 0:
col.addTerms(t[K][i], orders[i])
x[K] = master.addVar(obj=1, vtype="I", name="x(%s)"%K, column=col)
# master.write("MP" + str(iter) + ".lp")
K += 1
# Finally, solve the IP
# if LOG:
# master.Params.OutputFlag = 1 # verbose mode
master.optimize()
# if LOG:
# print
# print "final solution (integer master problem): objective =", master.ObjVal
# print "patterns:"
# for k in x:
# if x[k].X > EPS:
#.........这里部分代码省略.........