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Time-Scattered Heuristic for the Hardware Implementation of Population-Based ACO

  • Bernd Scheuermann
  • Michael Guntsch
  • Martin Middendorf
  • Hartmut Schmeck
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3172)

Abstract

We present a new kind of heuristic guidance as an extension to the Population-based Ant Colony Optimization (P-ACO) implemented in hardware on a Field Programmable Gate Array (FPGA). The heuristic information is obtained by transforming standard heuristic information into small time-scattered heuristic-vectors of favourable ant decisions. This approach is suited for heuristics which allow for an a priori calculation of the heuristics information. Using the proposed method, an ant can build-up a solution in quasi-linear time. Experimental studies measure the performance of the time-scattered heuristic. A comparison with the standard heuristic and candidate lists is also given.

Keywords

Field Programmable Gate Array Hardware Implementation Candidate List Heuristic Information Travel Salesperson 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

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Bernd Scheuermann
    • 1
  • Michael Guntsch
    • 1
  • Martin Middendorf
    • 2
  • Hartmut Schmeck
    • 1
  1. 1.Institute AIFBUniversity of KarlsruheGermany
  2. 2.Institute of Computer ScienceUniversity of LeipzigGermany

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