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Simulated Annealing Algorithm (simulated + annealing_algorithm)
Selected AbstractsWeb Discovery and Filtering Based on Textual Relevance Feedback LearningCOMPUTATIONAL INTELLIGENCE, Issue 2 2003Wai Lam We develop a new approach for Web information discovery and filtering. Our system, called WID, allows the user to specify long-term information needs by means of various topic profile specifications. An entire example page or an index page can be accepted as input for the discovery. It makes use of a simulated annealing algorithm to automatically explore new Web pages. Simulated annealing algorithms possess some favorable properties to fulfill the discovery objectives. Information retrieval techniques are adopted to evaluate the content-based relevance of each page being explored. The hyperlink information, in addition to the textual context, is considered in the relevance score evaluation of a Web page. WID allows users to provide three forms of the relevance feedback model, namely, the positive page feedback, the negative page feedback, and the positive keyword feedback. The system is domain independent and does not rely on any prior knowledge or information about the Web content. Extensive experiments have been conducted to demonstrate the effectiveness of the discovery performance achieved by WID. [source] Heuristic and simulated annealing algorithms for solving extended cell assignment problem in wireless ATM networksINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 1 2002Der-Rong Din Abstract In this paper, we investigate the extended cell assignment problem which optimally assigns new adding and splitting cells in Personal Communication Service (PCS) to switches in a wireless Asynchronous Transfer Mode (ATM) network. Given cells in a PCS network and switches on an ATM network (whose locations are fixed and known), we would like to do the assignment in an attempt to minimize a cost criterion. The cost has two components: one is the cost of handoffs that involve two switches, and the other is the cost of cabling. This problem is modeled as a complex integer programming problem, and finding an optimal solution to this problem is NP-hard. A heuristic algorithm and a simulated annealing algorithm are proposed to solve this problem. The heuristic algorithm, Extended Assignment Algorithm (EEA), consists of two phases, initial assigning phase and cell exchanging phase. First, in the initial assigning phase, the initial assignments of cells to switches are found. Then, these assignments are improved by performing cell exchanging phase in which two cells are repeatedly exchanged in different switches with great reduction of the total cost. The simulated annealing algorithm, ESA (enhanced simulated annealing), generates constraint-satisfied configurations, and uses three configuration perturbation schemes to change current configuration to a new one. Experimental results indicate that EAA and ESA algorithms have good performances. Copyright © 2002 John Wiley & Sons, Ltd. [source] Design of granule structure: Computational methods and experimental realizationAICHE JOURNAL, Issue 11 2006Mansoor A. Ansari Abstract The spatial distribution of solid components and porosity within a composite granule,its microstructure,is an important attribute as it carries information about the processing history of the granule and determines its end-use application properties, particularly the dissolution rate. In this work, the problem of rational design of granule structure is formulated, and two methods for its solution are proposed,stochastic design, which is based on random permutation of points within the structure using the simulated annealing algorithm, and variational design, which is based on direct simulation of granule formation from its constituent primary particles, followed by direct simulation of granule dissolution. The variational design method is demonstrated in a case study of the effect of primary particle size, radial distribution of components, and composition of a two-component granule (active, excipient) on the dissolution profile. Selected granule structures designed computationally were also physically made by fluid-bed granulation, their structure analyzed by X-ray micro-tomography, and dissolution curves measured. It was confirmed that the designed structures are feasible to manufacture and that they meet the required dissolution profiles. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source] Methodology for the optimal component selection of electronic devices under reliability and cost constraintsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 8 2007E. P. Zafiropoulos Abstract The objective of this paper is to present an efficient computational methodology for the reliability optimization of electronic devices under cost constraints. The system modeling for calculating the reliability indices of the electronic devices is based on Bayesian networks using the fault tree approach, in order to overcome the limitations of the series,parallel topology of the reliability block diagrams. Furthermore, the Bayesian network modeling for the reliability analysis provides greater flexibility for representing multiple failure modes and dependent failure events, and simplifies fault diagnosis and reliability allocation. The optimal selection of components is obtained using the simulated annealing algorithm, which has proved to be highly efficient in complex optimization problems where gradient-based methods can not be applied. The reliability modeling and optimization methodology was implemented into a computer program in Matlab using a Bayesian network toolbox. The methodology was applied for the optimal selection of components for an electrical switch of power installations under reliability and cost constraints. The full enumeration of the solution space was calculated in order to demonstrate the efficiency of the proposed optimization algorithm. The results obtained are excellent since a near optimum solution was found in a small fraction of the time needed for the complete enumeration (3%). All the optimum solutions found during consecutive runs of the optimization algorithm lay in the top 0.3% of the solutions that satisfy the reliability and cost constraints. Copyright © 2007 John Wiley & Sons, Ltd. [source] Structure and conformational analysis of a bidentate pro-ligand, C21H34N2S2, from powder synchrotron diffraction data and solid-state DFTB calculationsACTA CRYSTALLOGRAPHICA SECTION B, Issue 5 2009Edward E. Ávila The molecular and crystalline structure of ethyl 1,,2,,3,,4,,4a,,5,,6,,7,-octahydrodispiro[cyclohexane-1,2,-quinazoline-4,,1,,-cyclohexane]-8,-carbodithioate (I) was solved and refined from powder synchrotron X-ray diffraction data. The initial model for the structural solution in direct space using the simulated annealing algorithm implemented in DASH [David et al. (2006). J. Appl. Cryst.39, 910,915] was obtained performing a conformational study on the fused six-membered rings of the octahydroquinazoline system and the two spiran cyclohexane rings of (I). The best model was chosen using experimental evidence from 1H and 13C NMR [Contreras et al. (2001). J. Heterocycl. Chem.38, 1223,1225] in combination with semi-empirical AM1 calculations. In the refined structure the two spiran rings have the chair conformation, while both of the fused rings in the octahydroquinazoline system have half-chair conformations compared with in-vacuum density-functional theory (DFT) B3LYP/6-311G*, DFTB (density-functional tight-binding) theoretical calculations in the solid state and other related structures from X-ray diffraction data. Compound (I) presents weak intramolecular hydrogen bonds of the type N,H...S and C,H...S, which produce delocalization of the electron density in the generated rings described by graph symbols S(6) and S(5). Packing of the molecules is dominated by van der Waals interactions. [source] | |||||||||||||