doc/quicktour.dox
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Mon, 27 Jun 2005 15:25:33 +0000
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     1 /**
     2 
     3 \page quicktour Quick Tour to LEMON
     4 
     5 Let us first answer the question <b>"What do I want to use LEMON for?"
     6 </b>. 
     7 LEMON is a C++ library, so you can use it if you want to write C++ 
     8 programs. What kind of tasks does the library LEMON help to solve? 
     9 It helps to write programs that solve optimization problems that arise
    10 frequently when <b>designing and testing certain networks</b>, for example
    11 in telecommunication, computer networks, and other areas that I cannot
    12 think of now. A very natural way of modelling these networks is by means
    13 of a <b> graph</b> (we will always mean a directed graph by that and say
    14 <b> undirected graph </b> otherwise). 
    15 So if you want to write a program that works with 
    16 graphs then you might find it useful to use our library LEMON. LEMON 
    17 defines various graph concepts depending on what you want to do with the 
    18 graph: a very good description can be found in the page
    19 about \ref graphs "graphs".
    20 
    21 You will also want to assign data to the edges or nodes of the graph, for
    22 example a length or capacity function defined on the edges. You can do this in
    23 LEMON using so called \b maps. You can define a map on the nodes or on the edges of the graph and the value of the map (the range of the function) can be practically almost of any type. Read more about maps \ref maps-page "here".
    24 
    25 Some examples are the following (you will find links next to the code fragments that help to download full demo programs: save them on your computer and compile them according to the description in the page about \ref getsart How to start using LEMON):
    26 
    27 <ul>
    28 <li> First we give two examples that show how to instantiate a graph. The
    29 first one shows the methods that add nodes and edges, but one will
    30 usually use the second way which reads a graph from a stream (file).
    31 <ol>
    32 <li>The following code fragment shows how to fill a graph with data. It creates a complete graph on 4 nodes. The type Listgraph is one of the LEMON graph types: the typedefs in the beginning are for convenience and we will suppose them later as well.
    33  \code
    34   typedef ListGraph Graph;
    35   typedef Graph::NodeIt NodeIt;
    36 
    37   Graph g;
    38   
    39   for (int i = 0; i < 3; i++)
    40     g.addNode();
    41   
    42   for (NodeIt i(g); i!=INVALID; ++i)
    43     for (NodeIt j(g); j!=INVALID; ++j)
    44       if (i != j) g.addEdge(i, j);
    45  \endcode 
    46 
    47 See the whole program in file \ref helloworld.cc.
    48 
    49     If you want to read more on the LEMON graph structures and concepts, read the page about \ref graphs "graphs". 
    50 
    51 <li> The following code shows how to read a graph from a stream (e.g. a file). LEMON supports the DIMACS file format: it can read a graph instance from a file 
    52 in that format (find the documentation of the DIMACS file format on the web). 
    53 \code
    54 Graph g;
    55 std::ifstream f("graph.dim");
    56 readDimacs(f, g);
    57 \endcode
    58 One can also store network (graph+capacity on the edges) instances and other things in DIMACS format and use these in LEMON: to see the details read the documentation of the \ref dimacs.h "Dimacs file format reader".
    59 
    60 </ol>
    61 <li> If you want to solve some transportation problems in a network then 
    62 you will want to find shortest paths between nodes of a graph. This is 
    63 usually solved using Dijkstra's algorithm. A utility
    64 that solves this is  the \ref lemon::Dijkstra "LEMON Dijkstra class".
    65 The following code is a simple program using the \ref lemon::Dijkstra "LEMON
    66 Dijkstra class" and it also shows how to define a map on the edges (the length
    67 function):
    68 
    69 \code
    70 
    71     typedef ListGraph Graph;
    72     typedef Graph::Node Node;
    73     typedef Graph::Edge Edge;
    74     typedef Graph::EdgeMap<int> LengthMap;
    75 
    76     Graph g;
    77 
    78     //An example from Ahuja's book
    79 
    80     Node s=g.addNode();
    81     Node v2=g.addNode();
    82     Node v3=g.addNode();
    83     Node v4=g.addNode();
    84     Node v5=g.addNode();
    85     Node t=g.addNode();
    86 
    87     Edge s_v2=g.addEdge(s, v2);
    88     Edge s_v3=g.addEdge(s, v3);
    89     Edge v2_v4=g.addEdge(v2, v4);
    90     Edge v2_v5=g.addEdge(v2, v5);
    91     Edge v3_v5=g.addEdge(v3, v5);
    92     Edge v4_t=g.addEdge(v4, t);
    93     Edge v5_t=g.addEdge(v5, t);
    94   
    95     LengthMap len(g);
    96 
    97     len.set(s_v2, 10);
    98     len.set(s_v3, 10);
    99     len.set(v2_v4, 5);
   100     len.set(v2_v5, 8);
   101     len.set(v3_v5, 5);
   102     len.set(v4_t, 8);
   103     len.set(v5_t, 8);
   104 
   105     std::cout << "The id of s is " << g.id(s)<< std::endl;
   106     std::cout <<"The id of t is " << g.id(t)<<"."<<std::endl;
   107 
   108     std::cout << "Dijkstra algorithm test..." << std::endl;
   109 
   110     Dijkstra<Graph, LengthMap> dijkstra_test(g,len);
   111     
   112     dijkstra_test.run(s);
   113 
   114     
   115     std::cout << "The distance of node t from node s: " << dijkstra_test.dist(t)<<std::endl;
   116 
   117     std::cout << "The shortest path from s to t goes through the following nodes" <<std::endl;
   118  std::cout << " (the first one is t, the last one is s): "<<std::endl;
   119 
   120     for (Node v=t;v != s; v=dijkstra_test.predNode(v)){
   121 	std::cout << g.id(v) << "<-";
   122     }
   123     std::cout << g.id(s) << std::endl;	
   124 \endcode
   125 
   126 See the whole program in \ref dijkstra_demo.cc.
   127 
   128 The first part of the code is self-explanatory: we build the graph and set the
   129 length values of the edges. Then we instantiate a member of the Dijkstra class
   130 and run the Dijkstra algorithm from node \c s. After this we read some of the
   131 results. 
   132 You can do much more with the Dijkstra class, for example you can run it step
   133 by step and gain full control of the execution. For a detailed description, see the documentation of the \ref lemon::Dijkstra "LEMON Dijkstra class".
   134 
   135 
   136 <li> If you want to design a network and want to minimize the total length
   137 of wires then you might be looking for a <b>minimum spanning tree</b> in
   138 an undirected graph. This can be found using the Kruskal algorithm: the 
   139 class \ref lemon::Kruskal "LEMON Kruskal class" does this job for you.
   140 The following code fragment shows an example:
   141 
   142 Ide Zsuzska fog irni!
   143 
   144 <li>Many problems in network optimization can be formalized by means
   145 of a linear programming problem (LP problem, for short). In our
   146 library we decided not to write an LP solver, since such packages are
   147 available in the commercial world just as well as in the open source
   148 world, and it is also a difficult task to compete these. Instead we
   149 decided to develop an interface that makes it easier to use these
   150 solvers together with LEMON. The advantage of this approach is
   151 twofold. Firstly our C++ interface is more comfortable than the
   152 solvers' native interface. Secondly, changing the underlying solver in
   153 a certain software using LEMON's LP interface needs zero effort. So,
   154 for example, one may try his idea using a free solver, demonstrate its
   155 usability for a customer and if it works well, but the performance
   156 should be improved, then one may decide to purchase and use a better
   157 commercial solver.
   158 
   159 So far we have an
   160 interface for the commercial LP solver software \b CLPLEX (developed by ILOG)
   161 and for the open source solver \b GLPK (a shorthand for Gnu Linear Programming
   162 Toolkit).
   163 
   164 We will show two examples, the first one shows how simple it is to formalize
   165 and solve an LP problem in LEMON, while the second one shows how LEMON
   166 facilitates solving network optimization problems using LP solvers.
   167 
   168 <ol>
   169 <li>The following code shows how to solve an LP problem using the LEMON lp
   170 interface. The code together with the comments is self-explanatory.
   171 
   172 \code
   173 
   174   //A default solver is taken
   175   LpDefault lp;
   176   typedef LpDefault::Row Row;
   177   typedef LpDefault::Col Col;
   178   
   179 
   180   //This will be a maximization
   181   lp.max();
   182 
   183   //We add coloumns (variables) to our problem
   184   Col x1 = lp.addCol();
   185   Col x2 = lp.addCol();
   186   Col x3 = lp.addCol();
   187 
   188   //Constraints
   189   lp.addRow(x1+x2+x3 <=100);  
   190   lp.addRow(10*x1+4*x2+5*x3<=600);  
   191   lp.addRow(2*x1+2*x2+6*x3<=300);  
   192   //Nonnegativity of the variables
   193   lp.colLowerBound(x1, 0);
   194   lp.colLowerBound(x2, 0);
   195   lp.colLowerBound(x3, 0);
   196   //Objective function
   197   lp.setObj(10*x1+6*x2+4*x3);
   198   
   199   //Call the routine of the underlying LP solver
   200   lp.solve();
   201 
   202   //Print results
   203   if (lp.primalStatus()==LpSolverBase::OPTIMAL){
   204     printf("Z = %g; x1 = %g; x2 = %g; x3 = %g\n", 
   205 	   lp.primalValue(), 
   206 	   lp.primal(x1), lp.primal(x2), lp.primal(x3));
   207   }
   208   else{
   209     std::cout<<"Optimal solution not found!"<<std::endl;
   210   }
   211 
   212 
   213 \endcode
   214 
   215 See the whole code in \ref lp_demo.cc.
   216 
   217 <li>The second example shows how easy it is to formalize a max-flow
   218 problem as an LP problem using the LEMON LP interface: we are looking
   219 for a real valued function defined on the edges of the digraph
   220 satisfying the nonnegativity-, the capacity constraints and the
   221 flow-conservation constraints and giving the largest flow value
   222 between to designated nodes.
   223 
   224 In the following code we suppose that we already have the graph \c g,
   225 the capacity map \c cap, the source node \c s and the target node \c t
   226 in the memory. We will also omit the typedefs.
   227 
   228 \code
   229   //Define a map on the edges for the variables of the LP problem
   230   typename G::template EdgeMap<LpDefault::Col> x(g);
   231   lp.addColSet(x);
   232   
   233   //Nonnegativity and capacity constraints
   234   for(EdgeIt e(g);e!=INVALID;++e) {
   235     lp.colUpperBound(x[e],cap[e]);
   236     lp.colLowerBound(x[e],0);
   237   }
   238 
   239 
   240   //Flow conservation constraints for the nodes (except for 's' and 't')
   241   for(NodeIt n(g);n!=INVALID;++n) if(n!=s&&n!=t) {
   242     LpDefault::Expr ex;
   243     for(InEdgeIt  e(g,n);e!=INVALID;++e) ex+=x[e];
   244     for(OutEdgeIt e(g,n);e!=INVALID;++e) ex-=x[e];
   245     lp.addRow(ex==0);
   246   }
   247   
   248   //Objective function: the flow value entering 't'
   249   {
   250     LpDefault::Expr ex;
   251     for(InEdgeIt  e(g,t);e!=INVALID;++e) ex+=x[e];
   252     for(OutEdgeIt e(g,t);e!=INVALID;++e) ex-=x[e];
   253     lp.setObj(ex);
   254   }
   255 
   256   //Maximization
   257   lp.max();
   258 
   259   //Solve with the underlying solver
   260   lp.solve();
   261 
   262 \endcode
   263 
   264 The complete program can be found in file \ref lp_maxflow_demo.cc. After compiling run it in the form:
   265 
   266 <tt>./lp_maxflow_demo < ?????????.lgf</tt>
   267 
   268 where ?????????.lgf is a file in the lemon format containing a maxflow instance (designated "source", "target" nodes and "capacity" map).
   269 
   270 
   271 See the whole code in \ref lp_demo.cc.
   272 
   273 
   274 </ol>
   275 </ul>
   276 
   277 */