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Ant Colony Optimization

NS2 Project Report Download For Ant Colony Optimization are going to learn about the ACO (Ant Colony Optimization) techniques. ACO is one of the best shortest routing protocol.

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What is ACO?

The application of NS2 Project Report Download For Ant Colony Optimization is particularly interesting for

  1. NPhard problems, which cannot be efficiently solved by more traditional algorithms;
  2. Dynamic shortest path problems in which some properties of the problems change over time concurrently with the optimization process Ant algorithms were inspired by the observation of real ant colonies.

Applications of ACO:

  • For efficient scheduling.
  • Traveling salesman problems.
  • Constraint satisfaction.
  • Routing in telecommunication network.
  • Graph coloring.

Advantages of ACO:

  • Inherent parallelism.
  • Positive feedback accounts for rapid discovery of good solutions.
  • It can be used in dynamic applications.
  • Efficient for traveling salesman problems and similar problems.

Sample code for ACO:
void AntSense::trace (char *fmt,…){
va_list ap;
if (!tracetarget)
va_start (ap, fmt);
vsprintf (tracetarget->pt_->buffer (), fmt, ap);
tracetarget->pt_->dump ();
va_end (ap);
void AntSense::tracepkt (Packet * p, double now, int me, const char *type){
char buf[1024];
unsigned char *walk = p->accessdata ();
int ct = *(walk++);
int seq, dst, met;
snprintf (buf, 1024, “V%s %.5f _%d_ [%d]:”, type, now, me, ct);
while (ct–)
dst = *(walk++);
dst = dst << 8 | *(walk++);
dst = dst << 8 | *(walk++);
dst = dst << 8 | *(walk++);
met = *(walk++);
seq = *(walk++);
seq = seq << 8 | *(walk++);
seq = seq << 8 | *(walk++);


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