min cost max flow算法示例

时间:2024-08-12 18:35:08

问题描述

给定g个group,n个id,n<=g.我们将为每个group分配一个id(各个group的id不同)。但是每个group分配id需要付出不同的代价cost,需要求解最优的id分配方案,使得整体cost之和最小。

例子

例如以下4个group,三个id,value矩阵A

value id1 id2 id3
H1 4 3 0
H2 1 0 0
H3 2 0 2
H4 3 1 0

id_i分配给H_j的代价\(changing cost[i, j]=\sum(A[j,:])-A[j,i]\)。
例如,如果给H1指定id1,则value=4被保留,但是需要付出changing cost为3.

我们需要为H1-H4分别指定一个id1-id3,id4(新建的id),目标是是的总体的changing cost最小。
例子中最优的分配结果是:
H1 <- id2,
H2 <- New ID,
H3 <- id3,
H4 <- id1,
对应的changing cost=8 (4 + 1 + 2 + 1)。

Min-cost Max flow算法

Use min-cost max flow here
Connect source to all ids with capacity 1, connect each id to each h with capacity 1 and cost= -a[id[i], h[j]] (as you need to find maximums actually), and then connect all hs with sink with capacity 1.
After applying min-cost max flow, you will have flow in those (i, j) where you should assign i-th id to j-th h. New ids for other hs.

min cost max flow算法示例

因为capacity=1,算法最终结果f[i,j]只可能取值0/1。所以,如果f[i,j]=1,则id_i被分配给h_j.


Here is a possible solution of the problem with some help of [min cost max flow algorithm:
http://web.mit.edu/~ecprice/acm/acm08/MinCostMaxFlow.java https://en.wikipedia.org/wiki/Minimum-cost_flow_problem.

The basic idea is to translate consumer id, group id to vertex of graph, translate our constrains to constrains of MinCostMaxFlow problem.

As for POC, I used the source code from website (web.mit.edu), did some change and checked in the algorithm to trunk.
I added unit test RuleBasedOptimizerTest.test6() to test the 66x 4 case, which runs successfully in milliseconds.
Also, test was done on the data which caused time out before, and this time it is fast.

Steps of the algorithm:

Create the flow network:

  1. Introduce a source vertex, a sink vertex;
  2. Each consumerid is a vertex, each groupid is a vertex;
  3. Connect source to each consumerId, each edge has capacity 1;
  4. Connect each consumerId to groupId, each edge has capacity 1;
  5. Connect each groupId to sink, each edge has capacity 1;
  6. The cost of a(u, v) is from the cost table, but we need to take -1 x frequency.

Calculate max flow of the network, and get the flow matrix.

  • If there is flow from cid_i to gid_k then we assign the cid_i to the gid_k;
  • If there is no flow to gid_k, then we assign a new id to gid_k.

Algorithm complex

is O(min(|V|^2 * totflow, |V|^3 * totcost)), where |V|=(#groupid + #consumerId + 2).