All the needles in a haystack: Can exhaustive search overcome combinatorial chaos?

  • Jürg Nievergelt
  • Ralph Gasser
  • Fabian Mäser
  • Christoph Wirth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1000)


For half a century since computers came into existence, the goal of finding elegant and efficient algorithms to solve “simple” (welldefined and well-structured) problems has dominated algorithm design. Over the same time period, both processing and storage capacity of computers have increased roughly by a factor of 106. The next few decades may well give us a similar rate of growth in raw computing power, due to various factors such as continuing miniaturization, parallel and distributed computing. If a quantitative change of orders of magnitude leads to qualitative changes, where will the latter take place? Many problems exhibit no detectable regular structure to be exploited, they appear “chaotic”, and do not yield to efficient algorithms. Exhaustive search of large state spaces appears to be the only viable approach. We survey techniques for exhaustive search, typical combinatorial problems that have been solved, and present one case study in detail.


State Space Exhaustive Search Travel Salesman Problem Game Tree Forward Search 
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 1995

Authors and Affiliations

  • Jürg Nievergelt
    • 1
  • Ralph Gasser
    • 1
  • Fabian Mäser
    • 1
  • Christoph Wirth
    • 1
  1. 1.Department of Computer ScienceETH ZürichZürichSwitzerland

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