Search

In order to solve the problem that it is difficult to get out of the local optimum to achieve further optimization in large-scale dense Distributed Constraint Optimization Problems (DCOPs). This paper proposed a local parallel search framework (LPOS) for solving algorithms of DCOPs. In LPOS, the Agent searches all the value assignments of its local neighbors in parallel according to its current value assignment to further expand the search of solution space, so as to avoid the algorithm falling into local optimum prematurely. In order to ensure the convergence of the algorithm, this paper designed an adaptive equilibrium factor K to balance the exploration and exploitation ability of the DCOPs solving algorithms. At the theoretical analysis, it proved that the LPOS can expand the search of solution space and the K can achieve the balance. The experimental results demonstrate that the performance of the proposed LPOS is better than the-state-of-the-art algorithms in both low density and high density. Specifically, LPOS significantly superior to the competitors when solving high density DCOPs. [ABSTRACT FROM AUTHOR]

Fibonacci sequence is a classical sequence generated from the question of the rabbits' propagation. From the viewpoint of the rabbits' propagation, the classical Fibonacci sequence is generalized in many forms and some general forms are obtained. Combining interrelated knowledge of algebra and geometry by the transformation on k-dimensional space, the formula of general term for the generalized k-step Fibonacci sequence is obtained. The results show that the general term formula can be expressed by the solutions of the characteristic equation of the sequence. [ABSTRACT FROM AUTHOR]