Search results for " Annealing"
showing 10 items of 95 documents
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.
Substrate and atmosphere influence on oxygen p-doped graphene
2016
Abstract The mechanisms responsible for p-type doping of substrate supported monolayer graphene (Gr) by thermal treatments in oxygen ambient have been investigated by micro-Raman spectroscopy, atomic force microscopy (AFM) and X-ray Photoelectron Spectroscopy (XPS), considering commonly employed dielectric substrates, such as SiO 2 and Al 2 O 3 thin films grown on Si. While a high p-type doping (∼10 13 cm −2 ) is observed for Gr on SiO 2 , no significant doping is found for Gr samples on the Al 2 O 3 substrate, suggesting a key role of the Gr/SiO 2 interface states in the trapping of oxygen responsible for the Gr p-type doping. Furthermore, we investigated the doping stability of Gr on SiO…
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 …
Biased Modern Heuristics for the OCST Problem
2011
Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.
Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms
2019
In this paper, we try to find the most efficient optimization algorithm that can be used to resolve the hydropower optimization problem. We propose a novel optimization technique is called the Split-window method. The method is relatively simple and reduces the complexity of the optimization problem by split-ting the planning horizon (and datasets) into equal windows and assigning the same values to policies(actions) within each part. After splitting, a meta-heuristic technique is used to optimize the actions, and the dataset is split again until a split contains only one instance (timestep). The unique values to be optimized during each iteration is equal to the number of splits which make…
Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping
2013
This paper addresses the Network-on-Chip (NoC) application mapping problem. This is an NP-hard problem that deals with the optimal topological placement of Intellectual Property cores onto the NoC tiles. Network-on-Chip application mapping Evolutionary Algorithms are developed, evaluated and optimized for minimizing the NoC communication energy. Two crossover and one mutation operators are proposed. It is analyzed how each optimization algorithm performs with every genetic operator, in terms of solution quality and convergence speed. Our proposed operators are compared with state-of-the-art genetic operators for permutation problems. Finally, the problem is approached in a multi-objective w…