Exploiting ant synergy

• Initialization

  • Placing ants uniformily (rather than aggregated on individual nodes) resulted in superior performance.

• Employ ‘elitest’ (GAs) strategy

  • best-so-far trail is reinforced more than in the standard algorithm (ne - Q/L);
  • found optimal number of elitest ants.

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(elitest ants) Below optimal value increasing it results in discovery of better tours and/or the best tour being discovered earlier. Above it, the elitest ants force exploration around suboptimal tours in the early phase of search with resulting inferior performance.

For Oliver30, ne = 8 was optimal (in terms of time) although the range 2-16 could be tolerated.