This paper presents a new evolutionary method for solving the satissability problem. It is based on a parallel cellular genetic algorithm which performs global search on a random initial population of individuals and local selective generation of new strings according to new deened genetic operators. The algorithm adopts a diiusion model of information among chromosomes by realizing a two-dimen...

A new parallel hybrid method for solving the satissa-bility problem that combines cellular genetic algorithms and the random walk (W SAT) strategy of GSAT is presented. The method, called CGWSAT, uses a cellular genetic algorithm to perform a global search on a random initial population of candidate solutions and a local selective generation of new strings. Global search is specialized in local...

The cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. To enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. Normally, the parametersof the cuckoo search are kept constant. This may lead todecreasing the efficiency of the algorithm. To cop...

Visual localization to compute 6DoF camera pose from a given image has wide applications. Both local and global descriptors are crucial for visual localization. Most of the existing methods adopt two-stage strategy: retrieval first is performed by descriptors, then 2D-3D correspondences made 2D query points its nearest neighbor candidates which 3D visible these retrieved images. The above two s...

In this paper we propose a new parallel algorithm for solving global optimization (GO) multidimensional problems. The method unifies two powerful approaches for accelerating the search : parallel computations and local tuning on the behavior of the objective function. We establish convergence conditions for the algorithm and theoretically show that the usage of local information during the glob...