Exploiting Problem Structure in Combinatorial Landscapes: A Case Study
  on Pure Mathematics Application
  In this paper, we present a method using AI techniques to solve a case of
pure mathematics applications for finding narrow admissible tuples. The
original problem is formulated into a combinatorial optimization problem. In
particular, we show how to exploit the local search structure to formulate the
problem landscape for dramatic reductions in search space and for non-trivial
elimination in search barriers, and then to realize intelligent search
strategies for effectively escaping from local minima. Experimental results
demonstrate that the proposed method is able to efficiently find best known
solutions. This research sheds light on exploiting the local problem structure
for an efficient search in combinatorial landscapes as an application of AI to
a new problem domain.
