Titlebook: Global Optimization; Scientific and Engin János D. Pintér Book 2006 Springer-Verlag US 2006 Analysis.algorithm.algorithms.artificial neural

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Determining 3-D Structure of Spherical Viruses by Global Optimization,nimizing a weighted least squares error. Starting with random uniformly-distributed initial conditions, high quality reconstructions are achieved using GO algorithms. Similar quality reconstructions using classical multistart require initial conditions that incorporate more detailed . knowledge whic

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Improved Learning of Neural Nets Through Global Search, of an undesired local minimum. This chapter presents strategies for developing globally convergent modifications of local search methods and investigates the use of popular global search methods in neural network learning. The proposed methods tend to lead to desirable weight configurations and all

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Evolutionary Approach to Design Assembly Lines,ata preparation (2) elaboration of the logical layout of the line, which consists in the distribution of operations among stations along the line and an assignment of resources to the different stations and (3) finally the mapping phase, allowing to check the results with a commercial simulation pac

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Agroecosystem Management,t can be answered with this approach. The focus is laid on the estimation of optimum fertiliser input and crop rotation schemes as a dynamic control problem with different time scales. In this context mathematical properties of ecological models are discussed. Ecological models are heterogeneous in

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Optimization of Radiation Therapy Dose Delivery with Multiple Static Collimation, deliver the dose for a cancer patient. The MLC based techniques allow the construction of 3-dimensional and conformal dose distributions. The succesful use of MLC delivery method requires the global optimization of the treatment plan. The paper gives one potential approach to optimize the treatment

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1571-568X ial: .Optimization models based on a nonlinear systems description often possess multiple local optima. The objective of global optimization (GO) is to find the best possible solution of multiextremal problems. This volume illustrates the applicability of GO modeling techniques and solution strategi