This paper is an attempt to assess more precisely the scope of the multifractal approach for textural characterization. We perform a series of numerical experiments to reconstruct black and white images from the multiscale moments of a measure defined by a reference image. The reconstructed...

A problem often considered in Operations Research and Computational Physics is the traveling salesman problem, in which a traveling salesperson has to find the shortest closed tour between a given set of cities touching each city exactly once. The distances between the single nodes are known to...

By mapping the optimization problems to physical systems, the paper presents a general-purpose stochastic optimization method with extremal dynamics. It is built up with the traveling salesman problem (TSP) being a typical NP-complete problem. As self-organized critical processes of extremal...

Using a simple, annealed model, some of the key features of the recently introduced extremal optimization heuristic are demonstrated. In particular, it is shown that the dynamics of local search possesses a generic critical point under the variation of its sole parameter, separating phases of...

Identifying the community structure in a complex network has been addressed in many different ways. In this paper, the simulated annealing strategy is used to maximize the modularity of a network, associating with a dissimilarity-index-based and with a diffusion-distance-based k-means iterative...

Simulated annealing is the classic physical optimization algorithm, which has been applied to a large variety of problems for many years. Over time, several adaptive mechanisms for decreasing the temperature and thus controlling the acceptance of deteriorations have been developed, based on the...

We report a new statistical general property in traveling salesman problem, that the nth-nearest-neighbor distribution of optimal tours verifies with very high accuracy an exponential decay as a function of the order of neighbor n. Defining the energy function as deviation λ from this...

We apply simulated annealing to amino acid sequence alignment, a fundamental problem in bioinformatics, particularly relevant to evolution. Our goal was obtaining results comparable to those reached through dynamic programming algorithms, like the Needleman–Wunsch algorithm, as well as making...

We have developed continuous and discrete implementations of an optimization method (simulated annealing) to search the best way to fulfill different energy demands using different sets of transformation and storage devices. The simplicity of continuous description allows to implement the...

We discuss and illustrate a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so-called...