Search results for "simulated annealing"
showing 10 items of 63 documents
Predicting Heuristic Search Performance with PageRank Centrality in Local Optima Networks
2015
Previous studies have used statistical analysis of fitness landscapes such as ruggedness and deceptiveness in order to predict the expected quality of heuristic search methods. Novel approaches for predicting the performance of heuristic search are based on the analysis of local optima networks (LONs). A LON is a compressed stochastic model of a fitness landscape's basin transitions. Recent literature has suggested using various LON network measurements as predictors for local search performance.In this study, we suggest PageRank centrality as a new measure for predicting the performance of heuristic search methods using local search. PageRank centrality is a variant of Eigenvector centrali…
Exploring Multiobjective Optimization for Multiview Clustering
2018
We present a new multiview clustering approach based on multiobjective optimization. In contrast to existing clustering algorithms based on multiobjective optimization, it is generally applicable to data represented by two or more views and does not require specifying the number of clusters a priori . The approach builds upon the search capability of a multiobjective simulated annealing based technique, AMOSA, as the underlying optimization technique. In the first version of the proposed approach, an internal cluster validity index is used to assess the quality of different partitionings obtained using different views. A new way of checking the compatibility of these different partitioning…
An optimization approach for efficient management of EV parking lots with batteries recharging facilities
2013
In this paper an optimization approach to devise efficient management strategies for Electric Vehicles parking lots is proposed. A Monte Carlo approach is used to evaluate the load consumption profile for groups of Electric Vehicles showing different features. The Monte Carlo approach allows to combine the different social and economical features affecting the commercial penetration of Electric Vehicles with the technical aspects. The basic feature to be assessed is the initial State Of Charge, which in turn depends on the distance travelled by the vehicle since the last recharge and thus by the usage of the vehicle (private, professional). The model is then used to optimize some objective …
Inverse simulated annealing: Improvements and application to amorphous InSb
2014
An improved inverse simulated annealing method is presented to determine the structure of complex disordered systems from first principles in agreement with available experimental data or desired predetermined target properties. The effectiveness of this method is demonstrated by revisiting the structure of amorphous InSb. The resulting network is mostly tetrahedral and in excellent agreement with available experimental data.
Cu cluster shell structure at elevated temperatures
1991
Equilibrium structures of small (3--29)-atom Cu clusters are determined by simulated annealing, and finite-temperature ensembles are simulated by Monte Carlo techniques using the effective-medium theory for the energy calculation. Clusters with 8, 18, and 20 atoms are found to be particularly stable. The equilibrium geometrical structures are determined and found to be determined by a Jahn-Teller distortion, which is found to affect the geometry also at high temperatures. The ``magic'' clusters retain their large stability even at elevated temperatures.
A fast heuristic for solving the D1EC coloring problem
2010
In this paper we propose an efficient heuristic for solving the Distance-1 Edge Coloring problem (D1EC) for the on-the-fly assignment of orthogonal wireless channels in wireless as soon as a topology change occurs. The coloring algorithm exploits the simulated annealing paradigm, i.e., a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a sub optimal coloring scheme even for the case of dynamic channel allocation. However, a stateful implementation of the D1EC scheme is needed in order to speed-up the network coloring upon topology changes. In fact, a stateful D1EC reduces the algorithm’s convergen…
Time scales of adaptive behavior and motor learning in the presence of stochastic perturbations.
2009
In this paper, the major assumptions of influential approaches to the structure of variability in practice conditions are discussed from the perspective of a generalized evolving attractor landscape model of motor learning. The efficacy of the practice condition effects is considered in relation to the theoretical influence of stochastic perturbations in models of gradient descent learning of multiple dimension landscapes. A model for motor learning is presented combining simulated annealing and stochastic resonance phenomena against the background of different time scales for adaptation and learning processes. The practical consequences of the model's assumptions for the structure of pract…
Stochastic reconstruction of sandstones
2000
A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with prescribed two-point probability function, lineal path function, and ``pore size'' distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be s…
A novel heuristics-based energy management system for a multi-carrier hub enriched with solid hydrogen storage
2014
In this paper, an efficient optimization algorithm for the energy management of a grid-connected energy hub plant is proposed. The Simulated Annealing algorithm is adopted for the solution of the energy management problem aiming at the profit maximization for the owner of the energy hub plant. The use of a heuristic algorithm was required by the non-linearity of the efficiencies of each component in the energy transformation stages. The proposed heuristics is applied to a large energy hub, corresponding to the simulation of the test-bed that is being designed and developed inside the ongoing INGRID European research project.
Implementing some Evolutionary Computing Methods for Determining the Optimal Parameters in the Turning Process
2015
In this paper, we comparatively present two heuristics search methods – Simulated Annealing and Weighted Sum Genetic Algorithm, in order to find optimal cutting parameters in turning operation. We consider five different constraints aiming to achieve minimum total cost of machining. We developed a customizable software application in Microsoft Visual Studio with C# source code, flexible and extensible that implements the optimization methods. The experiments are based on real data gathered from S.C. “Compa” S.A Sibiu, a company that manufactures automotive components and targets improving of product quality and reducing cost and production time. The obtained results show that, although the …