نتایج جستجو برای Simulated Annealing Algorithm

تعداد نتایج: 685003  

2010
Dr. Rana, Fareed Ghani,

Received on:2/6/2009 Accepted on:1/4/2010 Abstract Simulated annealing (SA) has been considered as a good tool for search and optimization problems which represent the abstraction of obtaining the crystalline structure through a physical process. This algorithm works sequentially that the current state will produce only one next state. That will make the search to be slower and the important dr...

M.A Gutiérrez-Andrade, P Lara-Velázquez, S.G de-los-Cobos-Silva,

The Robust Coloring Problem (RCP) is a generalization of the well-known Graph Coloring Problem where we seek for a solution that remains valid when extra edges are added. The RCP is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. This problem has been proved as NP-hard and in instances larger than 30 vertices, meta-...

Journal: :تحقیقات مالی 0
سعید قدوسی, کارشناس‎ارشد مدیریت مالی، دانشگاه تهر..., دانشیار مدیریت مالی، دانشکدۀ مدیریت د..., دانشیار مهندسی صنایع، دانشکدۀ فنی دان...,

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

1995
Jurij Silc,

This paper presents a parallel simulated annealing algorithm for solving the problem of mapping irregular parallel programs onto homogeneous processor arrays with regular topology. The algorithm constructs and uses joint transformations. These transformations guarantee a high degree of parallelism that is bounded below by d jNpj deg(Gp)+1 e, where jN p j is the number of task nodes in the mappe...

1995
Samir W. Mahfoud, David E. Goldberg,

This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic algorithms, an eeective combination of simulated annealing and genetic algorithms, called parallel recombinative simulated annealing, is developed. This new algorithm strives to retain the desirable asymptotic convergence properties of simulated annealing, while adding the populations approach an...

,

The Network Design Problem (NDP) is one of the important problems in combinatorial optimization. Among the network design problems, the Multicommodity Capacitated Network Design (MCND) problem has numerous applications in transportation, logistics, telecommunication, and production systems. The MCND problems with splittable flow variables are NP-hard, which means they require exponential time t...

B. Minaee, , L. Sadat Taghavi, , M. Nasiri, ,

Abstract as a single objective one. Measures like support, confidence and other interestingness criteria which are used for evaluating a rule, can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions that exist in the rule. This objective represents the accuracy of the rules extracted from the da...

Journal: :CoRR 2017
Alper Kose, Berke Aral Sonmez, Metin Balaban,

The goal of this Random Walks project is to code and experiment the Markov Chain Monte Carlo (MCMC) method for the problem of graph coloring. In this report, we present the plots of cost function H by varying the parameters like q (Number of colors that can be used in coloring) and c (Average node degree). The results are obtained by using simulated annealing scheme, where the temperature (inve...

2010
Enlu Zhou, Xi Chen,

In this paper, we propose sequential Monte Carlo simulated annealing (SMC-SA), a populationbased simulated annealing algorithm, for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing, such that the empirical distribution will converge weakly to the uniform distribution on the se...

2010
Hong Guo, Martin Zuckermann, R. Harris, Martin Grant,

We present a new deterministic algorithm for simulated annealing and demonstrate its applicability with several classical examples: the ground state energies of the 2d and 3d short range king spin glasses, the traveling salesman problem, and pattern recognition in computer vision. Our algorithm is based on a microcanonical Monte Carlo method and is shown to be a powerful tool for the analysis o...

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