Proceedings ArticleDOI
Parallel simulated annealing with adaptive temperature determined by genetic algorithm
Mitsunori Miki,Tomoyuki Hiroyasu,Takeshi Yoshida,Toshihiko Fushimi +3 more
- Vol. 3, pp 6
TLDR
The proposed method is applied to solve many TSPs (Traveling Salesman Problems), and it is found that the method is very effective and useful.Abstract:
Simulated annealing (SA) is an effective general heuristic method for solving many combinatorial optimization problems. This paper deals with the two problems in SA. One is the long computational time of the numerical annealings, and the solution to it is the parallel processing of SA. The other one is the determination of the appropriate temperature schedule in SA, and the solution to it is the introduction of an adaptive mechanism for changing the temperature. The multiple SA processes are performed in multiple processors, and the temperatures in the SA processes are determined by a genetic algorithms. The proposed method is applied to solve many TSPs (Traveling Salesman Problems), and it is found that the method is very effective and useful.read more
Citations
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Journal ArticleDOI
Distributed Particle Swarm Optimization and Simulated Annealing for Energy-efficient Coverage in Wireless Sensor Networks
TL;DR: Simulations of wireless sensor node deployment verify that coverage performance can be guaranteed, energy consumption of communication is conserved after deployment optimization and the optimization performance is boosted by the distributed algorithm.
JournalDOI
Una mirada acerca del rol docente universitario, desde las prácticas de la enseñanza en entornos no presenciales.
TL;DR: This paper present a resumen de la tesis doctoral desarrollada a partir de una hipotesis subyacente: el reemplazo del entorno tradicional de la ensenanza universitaria by un entorno no presencial, produciria en los docentes the necesidad de replantear sus practicas of the enenanza apuntando a transformar el modelo dominante; en tanto la sustitucion de la clase como lugar of encuentro real ent
Book ChapterDOI
GPU Parallel Computation in Bioinspired Algorithms: A Review
TL;DR: This chapter reviews the use of GPUs to solve scientific problems, giving an overview of current software systems.
Dissertation
A study of Population MCMC for estimatingBayes Factors over nonlinear ODE models
TL;DR: In this paper, the authors investigate tools for calculating Bayes factors to distinguish between ODE-based clock oscillator models of varying complexity, which form the basic building blocks for describing this ubiquitous circadian behaviour.
Journal Article
Detailed Analysis of Uphill Moves in Temperature Parallel Simulated Annealing and Enhancement of Exchange Probabilities
Yang Jun,Satoshi Mizuta +1 more
TL;DR: It is demonstrated that the probability of the occurrence of uphill moves in temperature parallel simulated annealing is so small that the effects of parallelization might be lost when the number of processing nodes is small.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book ChapterDOI
Real-Coded Genetic Algorithms and Interval-Schemata
Larry Eshelman,J. David Schaffer +1 more
TL;DR: It is shown how interval-schemata are analogous to Holland's symbol- schemata and provide a key to understanding the implicit parallelism of real-valued GAs and support the intuition that real-coded GAs should have an advantage over binary coded GAs in exploiting local continuities in function optimization.
Journal ArticleDOI
Very fast simulated re-annealing
TL;DR: An algorithm is developed to statistically find the best global fit of a nonlinear nonconvex cost-function over a D-dimensional space and it is argued that this algorithm permits an annealing schedule for ''temperature'' T decreasing exponentially in annealed-time k, T = T"0exp(-ck^1^/^D).