Search results for " simulated annealing"
showing 10 items of 14 documents
Domain-Knowledge Optimized Simulated Annealing for Network-on-Chip Application Mapping
2013
Network-on-Chip architectures are scalable on-chip interconnection networks. They replace the inefficient shared buses and are suitable for multicore and manycore systems. This paper presents an Optimized Simulated Annealing (OSA) algorithm for the Network-on-Chip application mapping problem. With OSA, the cores are implicitly and dynamically clustered using knowledge about communication demands. We show that OSA is a more feasible Simulated Annealing approach to NoC application mapping by comparing it with a general Simulated Annealing algorithm and a Branch and Bound algorithm, too. Using real applications we show that OSA is significantly faster than a general Simulated Annealing, withou…
A new innovative cooling law for simulated annealing algorithms
2015
The present paper proposes an original and innovative cooling law in the field of Simulated Annealing (SA) algorithms. Particularly, such a law is based on the evolution of different initial seeds on which the algorithm works in parallel. The efficiency control of the new proposal, executed on problems of different kind, shows that the convergence quickness by using such a new cooling law is considerably greater than that obtained by traditional laws. Furthermore, it is shown that the effectiveness of the SA algorithm arising from the proposed cooling law is independent of the problem type. This last feature reduces the number of parameters to be initially fixed, so simplifying the prelimin…
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…
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 …
A heuristic for fast convergence in interference-free channel assignment using D1EC coloring
2010
This work proposes an efficient method for solving the Distance-1 Edge Coloring problem (D1EC) for the assignment of orthogonal channels in wireless networks with changing topology. The coloring algorithm is performed by means of the simulated annealing method, a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a suboptimal coloring scheme. Furthermore, a stateful implementation of the D1EC scheme is proposed, in which network coloring is executed upon topology changes. The stateful D1EC is also based on simulated annealing and reduces the algorithm’s convergence time by one order of magnitude in …
Simulated Annealing in Bayesian Decision Theory
1992
Since the seminal paper by Kirkpatrick, Gelatt and Vechhi (1983), a number of papers in the scientific literature refer to simulated annealing as a powerful random optimization method which promises to deliver, within reasonable computing times, optimal or nearly optimal solutions to complex decision problems hitherto forbidding. The algorithm, which uses the physical process of annealing as a metaphor, is special in that, at each iteration, one may move with positive probability to solutions with higher values of the function to minimize, rather than directly jumping to the point with the smallest value within the neighborhood, thus drastically reducing the chances of getting trapped in lo…
Design of the Tube Roll Forming Process Through an Heuristic Algorithm
2002
In the paper the design of an industrial tube roll forming process is developed utilizing an heuristic algorithm, namely the simulated annealing (SA). In particular both the number and the shape of the deforming rolls are determined in order to define the forming sequence. The effectiveness of the results supplied by the SA algorithm is verified both by means of some experiments tests carried out on an industrial tube roll forming equipment and through a set of numerical simulations of the process.
Simulated Annealing Technique for Fast Learning of SOM Networks
2011
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensi…
Improved SOM Learning using Simulated Annealing
2007
Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparis…