Resources

Traveling Salesman Problem (misole04)

/*****************************************************************/
/*                                                               */
/*          S A S   S A M P L E   L I B R A R Y                  */
/*                                                               */
/*    NAME: misole04                                             */
/*   TITLE: Traveling Salesman Problem (misole04)                */
/* PRODUCT: OR                                                   */
/*  SYSTEM: ALL                                                  */
/*    KEYS: OR                                                   */
/*   PROCS: OPTMODEL, GPLOT                                      */
/*    DATA:                                                      */
/*                                                               */
/* SUPPORT:                             UPDATE:                  */
/*     REF:                                                      */
/*    MISC: Example 4 from the Mixed Integer Linear Programming  */
/*          Solver chapter of Mathematical Programming.          */
/*                                                               */
/*****************************************************************/


/*
%let tsplib = location-of-st70-problem
*/

/* convert the TSPLIB instance into a data set */
data tspData(drop=H);
   infile "&tsplib";
   input H $1. @;
   if H not in ('N','T','C','D','E');
   input @1 var1-var3;
run;


/* direct solution using the MTZ formulation */
proc optmodel;
   set VERTICES;
   set EDGES = {i in VERTICES, j in VERTICES: i ne j};
   num xc {VERTICES};
   num yc {VERTICES};
   /* read in the instance and customer coordinates (xc, yc) */
   read data tspData into VERTICES=[_n_] xc=var2 yc=var3;
   /* the cost is the euclidean distance rounded to the nearest integer */
   num c {<i,j> in EDGES}
       init floor( sqrt( ((xc[i]-xc[j])**2 + (yc[i]-yc[j])**2)) + 0.5);
   var x {EDGES} binary;
   var u {i in 2..card(VERTICES)} >= 2 <= card(VERTICES);
   /* each vertex has exactly one in-edge and one out-edge */
   con assign_i {i in VERTICES}:
       sum {j in VERTICES: i ne j} x[i,j] = 1;
   con assign_j {j in VERTICES}:
       sum {i in VERTICES: i ne j} x[i,j] = 1;
   /* minimize the total cost */
   min obj
       = sum {<i,j> in EDGES} (if i > j then c[i,j] else c[j,i]) * x[i,j];
   /* no subtours */
   con mtz {<i,j> in EDGES : (i ne 1) and (j ne 1)}:
       u[i] - u[j] + 1 <= (card(VERTICES) - 1) * (1 - x[i,j]);
   solve with milp / maxtime = 600;
quit;

/* iterative solution using the subtour formulation */
proc optmodel;
   set VERTICES;
   set EDGES = {i in VERTICES, j in VERTICES: i > j};
   num xc {VERTICES};
   num yc {VERTICES};

   num numsubtour init 0;
   set SUBTOUR {1..numsubtour};

   /* read in the instance and customer coordinates (xc, yc) */
   read data tspData into VERTICES=[var1] xc=var2 yc=var3;

   /* the cost is the euclidean distance rounded to the nearest integer */
   num c {<i,j> in EDGES}
       init floor( sqrt( ((xc[i]-xc[j])**2 + (yc[i]-yc[j])**2)) + 0.5);

   var x {EDGES} binary;

   /* minimize the total cost */
   min obj =
       sum {<i,j> in EDGES} c[i,j] * x[i,j];

   /* each vertex has exactly one in-edge and one out-edge */
   con two_match {i in VERTICES}:
       sum {j in VERTICES: i > j} x[i,j]
     + sum {j in VERTICES: i < j} x[j,i] = 2;

   /* no subtours (these constraints are generated dynamically) */
   con subtour_elim {s in 1..numsubtour}:
       sum {<i,j> in EDGES: (i in SUBTOUR[s] and j not in SUBTOUR[s])
          or (i not in SUBTOUR[s] and j in SUBTOUR[s])} x[i,j] >= 2;

   /* this starts the algorithm to find violated subtours */
   set <num,num> EDGES1;
   set VERTICES1 = union{<i,j> in EDGES1} {i, j};
   num component {VERTICES1};
   num numcomp  init 2;
   num iter     init 1;
   num numiters init 1;
   set ITERS = 1..numiters;
   num sol {ITERS, EDGES};

   /* initial solve with just matching constraints */
   solve;
   call symput(compress('obj'||put(iter,best.)),
              trim(left(put(round(obj),best.))));
   for {<i,j> in EDGES} sol[iter,i,j] = round(x[i,j]);

   /* while the solution is disconnected, continue */
   do while (numcomp > 1);
      iter = iter + 1;

      /* find connected components of support graph   */
      EDGES1 = {<i,j> in EDGES: round(x[i,j].sol) = 1};
      solve with network /
         links   = (include=EDGES1)
         nodes   = (include=VERTICES1)
         concomp
         out     = (concomp=component);

      numcomp = _oroptmodel_num_["NUM_COMPONENTS"];
      if numcomp = 1 then leave;
      numiters = iter;
      numsubtour = numsubtour + numcomp;
      for {comp in 1..numcomp} do;
         SUBTOUR[numsubtour-numcomp+comp]
           = {i in VERTICES: component[i] = comp};
      end;

      solve;
      call symput(compress('obj'||put(iter,best.)),
                 trim(left(put(round(obj),best.))));
      for {<i,j> in EDGES} sol[iter,i,j] = round(x[i,j]);
   end;

   /* create a data set for use by sgplot */
   create data solData from
      [iter i j]={it in ITERS, <i,j> in EDGES: sol[it,i,j] = 1}
      x1=xc[i] y1=yc[i] x2=xc[j] y2=yc[j];
   call symput('numiters',put(numiters,best.));
quit;


%macro plotTSP;
   %do i = 1 %to &numiters;
      /* create annotate data set to draw subtours */
      data anno(drop=iter);
         retain drawspace 'datavalue' linethickness 1 function 'line';
         set solData;
         where iter = &i;
      run;

      title1 h=2 "TSP: Iter = &i, Objective = &&obj&i";
      title2;

      proc sgplot data=tspData sganno=anno;
         scatter x=var2 y=var3 / datalabel=var1;
         xaxis display=none;
         yaxis display=none;
      run;
   %end;
%mend plotTSP;

%plotTSP;