In this paper, we propose a new probabilistic sampling procedure and its application in simulated annealing (SA). The new procedure uses Bayesian analysis to evaluate samples made already and draws the next sample based on a density function constructed through Bayesian analysis. After integrating our procedure in SA, we apply it to solve a set of optimization benchmarks. Our results show that ...

The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the ...

Most of graph drawing algorithms draw graphs on unbounded planes. In this paper we introduce a new polyline grid drawing algorithm for drawing free trees on plane regions which are bounded by simple polygons. Our algorithm uses the simulated annealing (SA) method, and by means of the straight skeletons of the bounding polygons guides the SA method to uniformly distribute the vertices of the giv...

In this paper we propose a new hybrid algorithm for solving the Unit Commitment Problem (UCP). The algorithm integrates the use of Simulated Annealing (SA) and Tabu Search (TS) for solving the UCP. The algorithm includes a step to find an initial control parameter, at which virtually all trial solutions are accepted. It uses a polynomial-time cooling schedule that is advocated in the SA literat...

Sometimes, it is difficult to cope with a good set of values for the parameters of an algorithm that solves an specific optimization problem. This work presents a methodology for fine-tuning the parameters of a Simulated Annealing (SA) algorithm solving the Bridge Club (BC) problem. The methodology uses Covering Arrays as a tool that evaluates a set of values for the parameters of the SA so tha...

Simulated Annealing (SA) is a powerful stochastic search method that can produce very high quality solutions for hard combinatorial optimization problem. In this paper, we applied this SA method to optimize our 3D hierarchical reconstruction neural network (NN). This NN deals with complicated task to reconstruct a complete representation of a given object relying only on a limited number of vie...

this study is devoted to the formulation of the network design problem of one-way streets and the application of simulated annealing (sa) algorithm to solve this problem for a large real network. it discusses some points of views on one-way street networks, the objective function used for design, the way in which design constraints may be considered, and the traffic problems concerning one-way ...

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrat...