# Boost :

Subject: [boost] BGL
From: Sultana Rashid (sultana32_at_[hidden])
Date: 2011-04-17 06:49:41

Hi all,
I have submitted two proposals to Boost.I am very interested in C++ works
and algorithms,so I submitted only for Boost projects.I met an accident
after proposal submission so that I could not refine my project ideas.Now I
am well and have enough free time to interact with mentors and do the
necessary works.My proposals can be found here:

Now I am writing something about one of my algorithms' prospective design.

*Dinitz blocking max flow algorithm:*
*Input:* Graph& g .A directed graph. The graph's type will be a model of
VertexListGraph and IncidenceGraph.

*Input:* *source node* which is a vertex. Its type will be graph's vertex
descriptor type.

*Input:* *sink node* ,its type will be same as source node.

*Input:* capacity map(CapacityEdgeMap cap),the edge capacity property map.
The type must be a model of a constant Lvalue Property Map. The key type of
the map must be the graph's edge descriptor type.
Default: get(edge_capacity, g)

*Input:* reverse edge map(ReverseEdgeMap rev) An edge property map that maps
every edge (u,v) in the graph to the reverse edge (v,u). The map must be a
model of constant Lvalue Property Map. The key type of the map must be the
graph's edge descriptor type.
Default: get(edge_reverse, g)

*Input:*residual capacity map(ResidualCapacityEdgeMap res) ,This maps edges
to their residual capacity. The type must be a model of a mutable Lvalue
Property Map. The key type of the map must be the graph's edge descriptor
type.
Default: get(edge_residual_capacity, g)
At first the whole capacity will be the residual capacity,then after every
phase of calculation it will act as output.

*Input:* vertex index(VertexIndexMap index_map)
Maps each vertex of the graph to a unique integer in the range [0,
num_vertices(g)). The map must be a model of constant LvaluePropertyMap. The
key type of the map must be the graph's vertex descriptor type.
Default: get(vertex_index, g)

*Output:*The total flow of the network,flow in every iteration and min cut.

*** User will be able to use the algorithm in two ways, named parameter
version and non-named parameter version.*
*** In named parameter version,explicit inputs will be the graph,source and
sink node.Other will be default params.
*
*** In non-named parameter version,all will be explicitly input.
*
*
*
I studied already implemented flow algorithms and took help.But I am in