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Programming and Computer Software

, Volume 31, Issue 4, pp 167–178 | Cite as

Ant Algorithms: Theory and Applications

  • S. D. Shtovba
Article

Abstract

This paper reviews the theory and applications of ant algorithms, new methods of discrete optimization based on the simulation of self-organized colony of biologic ants. The colony can be regarded as a multi-agent system where each agent is functioning independently by simple rules. Unlike the nearly primitive behavior of the agents, the behavior of the whole system happens to be amazingly reasonable. The ant algorithms have been extensively studied by European researchers from the mid-1990s. These algorithms have successfully been applied to solving many complex combinatorial optimization problems, such as the traveling salesman problem, the vehicle routing problem, the problem of graph coloring, the quadratic assignment problem, the problem of network-traffic optimization, the job-shop scheduling problem, etc. The ant algorithms are especially efficient for online optimization of processes in distributed nonstationary systems (for example, telecommunication network routing).

Keywords

Schedule Problem Assignment Problem Travel Salesman Problem Simple Rule Combinatorial Optimization Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© MAIK “Nauka/Interperiodica” 2005

Authors and Affiliations

  • S. D. Shtovba
    • 1
  1. 1.Vinnitsa State Technical UniversityVinnitsaUkraine

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