通过元组迭代 - 网络流动

Question

希望提供一些帮助，试图定义一个函数，该功能可以通过创建网络流量来确定团队何时被取消，我可以肯定的是我几乎在那里，但是似乎有一个错误，我缺少了我＆amp＆amp;无法弄清楚它是什么？ 任何帮助都将受到赞赏！！！

最初的问题：

在下面完成team_elimined功能，该功能将存储在team的团队名称和wins，， games_to_play字典（上面是Compute_numbers函数的输出），并检查该团队是否被删除。您的功能应返回布尔值true如果团队被取消，false如果否则。

这是定义函数

def team_elimined（团队，获胜，games_to_play）：

## Compute the best possible win total for the given team
W = wins[team] + sum([games_to_play[p] for p in games_to_play if p[0] == team or p[1] == team])

## Construct sets which don't contain the team
teamlist = [t for t in wins if t != team]
pairs = [p for p in games_to_play if p[0] != team and p[1] != team]

## Construct the index sets for the x variables
idx = [(h, a, h) for h, a in pairs] + [(h, a, a) for h, a in pairs]

## Boolean variable that you need to modify
team_eliminated = None

nodes = ['s', 't'] + [i for i in pairs] + [j for j in teamlist]

arcs = ({((k[0], k[1]), k[2]) for k in idx})

arcs.update({('s', i): games_to_play[i] for i in games_to_play})

arcs.update({(j, 't'): wins[j] for j in wins})

arcs.update({('t','s'): GRB.INFINITY})

outgoing = {i:[j for j in nodes if (((k[0],k[1]), k[2]) for k in idx) in arcs] for i in nodes}
incoming = {i:[j for j in nodes if ((k[2], (k[0],k[1])) for k in idx) in arcs] for i in nodes}

mod = gp.Model('team-eliminated')

x = mod.addVars(arcs, lb=0, ub=arcs, vtype=GRB.CONTINUOUS, name='x')

for i in nodes : 
    mod.addConstr(gp.quicksum(x[i,j] for j in outgoing[i]) - gp.quicksum(x[j,i] for j in incoming[i]) == 0)

mod.setObjective(x['t', 's'], sense=GRB.MINIMIZE)

mod.update()
mod.optimize()

return team_eliminated

这是实现上述

def who_teams_remaining

remaining = []
eliminated = []
for t in wins:
    elim = team_eliminated(t, wins, games_to_play)
    if (elim):
        eliminated.append(t)
    else:
        remaining.append(t)
return remaining, eliminated

的函数： 在此处输入图像描述

Answer 1

我没有在所有这些方面遇到错误，除了凹痕以外没有更改：

def team_eliminated(team, wins, games_to_play):

    ## Compute the best possible win total for the given team
    W = wins[team] + sum([games_to_play[p] for p in games_to_play if p[0] == team or p[1] == team])

    ## Construct sets which don't contain the team
    teamlist = [t for t in wins if t != team]
    pairs = [p for p in games_to_play if p[0] != team and p[1] != team]

    ## Construct the index sets for the x variables
    idx = [(h, a, h) for h, a in pairs] + [(h, a, a) for h, a in pairs]

    ## Boolean variable that you need to modify
    team_eliminated = None

    nodes = ['s', 't'] + [i for i in pairs] + [j for j in teamlist]

    arcs = ({((k[0], k[1]), k[2]) for k in idx})

    arcs.update({('s', i): games_to_play[i] for i in games_to_play})

    arcs.update({(j, 't'): wins[j] for j in wins})

    arcs.update({('t','s'): GRB.INFINITY})

    outgoing = {i:[j for j in nodes if (((k[0],k[1]), k[2]) for k in idx) in arcs] for i in nodes}
    incoming = {i:[j for j in nodes if ((k[2], (k[0],k[1])) for k in idx) in arcs] for i in nodes}

    mod = gp.Model('team-eliminated')

    x = mod.addVars(arcs, lb=0, ub=arcs, vtype=GRB.CONTINUOUS, name='x')

    for i in nodes : 
        mod.addConstr(gp.quicksum(x[i,j] for j in outgoing[i]) - gp.quicksum(x[j,i] for j in incoming[i]) == 0)

    mod.setObjective(x['t', 's'], sense=GRB.MINIMIZE)

    mod.update()
    mod.optimize()

    return team_eliminated, wins


def which_teams_remaining(wins, games_to_play):
   
    remaining = []
    eliminated = []
    for t in wins:
        elim = team_eliminated(t, wins, games_to_play)
        if (elim):
            eliminated.append(t)
        else:
            remaining.append(t)
    return remaining, eliminated