mutual information (mi) is a widely used similarity metric for multimodality image registration. however, it involves an extremely high computational time especially when it is applied to volume images. moreover, its robustness is affected by existence of local maxima. the multi-resolution pyramid approaches have been proposed to speed up the registration process and increase the accuracy of th...

In today’s economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in product mix and demand. Therefore, this paper considers the problem of arranging and rearranging (when there are changes between the flows of materials between departments) manufacturing facilities such that sum of the material handling and rearrangement costs are minimized. This probl...

In this paper, we propose a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and on Simulated Annealing (SA) for reducing memory energy consumption in embedded systems. Our hybrid algorithm outperforms the Tabu Search (TS) approach. In fact, nearly from 76% up to 98% less energy consumption is recorded.

We will present an algorithm, based on SA-techniques and a sampling procedure, that colors a given random 3-colorable graph with high probability in sublinear time. This result is the rst theoretical justiication of many excellent experimental performance results of Simulated Annealing 10, 17] applied to graph coloring problems.

This work presents a heuristic approach proposed by one of the finalists of the Third International Timetabling Competition (ITC2011). The KHE school timetabling engine is used to generate an initial solution and then Simulated Annealing (SA) and Iterated Local Search (ILS) perform local search around this solution.

A modification of the standard Simulated Annealing (SA) algorithm is presented for finding the global minimum of a continuous multidimensional, multimodal function. We report results of computational experiments with a set of test functions and we compare to methods of similar structure. The accompanying software accepts objective functions coded both in Fortran 77 and C++.

For the optimal size and placement of the dynamic voltage restorer (DVR) in a distribution network, in this paper the Simulated Annealing (SA) method is proposed. The multi-objective problem is converted to a single function using the goal attainment method. The obtained results show the voltage sag improvement on sensitive load nodes and other nodes in distribution system with minimum cost.

This paper presents a modified particle swarm optimization (PSO) with simulated annealing (SA) technique. An improved PSO-based artificial neural network (ANN) is developed. The results show that the proposed SAPSO-based ANN has a better ability to escape from a local optimum and is more effective than the conventional PSO-based ANN. r 2004 Elsevier B.V. All rights reserved.