Volume 9 (2018) Issue 1 Pages 95-106
Combinatorial optimization problems consist of static problems such as the traveling salesman problem and the quadratic assignment problem, and dynamic problems such as the packet routing problem and the traffic flow control problem. In static combinatorial optimization problems, the search space for the solution does not change over time and, therefore, neither does the optimal solution. On the contrary, in dynamic combinatorial optimization problems, the search space always changes. Thus, there is no guarantee that the optimal solution for one iteration also applies to the next iteration. In the context of dynamic combinatorial optimization problems, we propose in this paper a heuristic routing method that uses chaotic neurodynamics and degree information to solve the packet routing problem. Numerical experiments showed that the proposed method improves average arrival rate by approximately 130% over the conventional shortest hop method.