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Global Optimization: Scientific and Engineering Case Studies Book

Global Optimization: Scientific and Engineering Case Studies
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  • Global Optimization: Scientific and Engineering Case Studies
  • Written by author Janos D. Pinter
  • Published by Springer-Verlag New York, LLC, July 2006
  • 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. Global Optimization: Selected Case Studies ill
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Ch. 1Global optimization in solvent design1
Ch. 2Feeding strategies for maximising gross margin in pig production33
Ch. 3Optimized design of dynamic networks with heuristic algorithms45
Ch. 4A new smoothing-based global optimization algorithm for protein conformation problems73
Ch. 5Physical perspectives on the global optimization of atomic clusters103
Ch. 6Efficient global geometry optimization of atomic and molecular clusters141
Ch. 7Computational analysis of human DNA sequences : an application of artificial neural networks169
Ch. 8Determination of a laser cavity field solution using global optimization181
Ch. 9Computational experience with the molecular distance geometry problem213
Ch. 10Non-linear optimization models in water resource systems227
Ch. 11Solving the phase unwrapping problem by a parameterized network optimization approach243
Ch. 12Evolutionary algorithms for global optimization267
Ch. 13Determining 3-D structure of spherical viruses by global optimization301
Ch. 14A collaborative solution methodology for inverse position problem331
Ch. 15Improved learning of neural nets through global search361
Ch. 16Evolutionary approach to design assembly lines389
Ch. 17Agroecosystem management413
Ch. 18Finding the minimal root of an equation - applications and algorithms based on lipschitz condition441
Ch. 19Optimization of radiation therapy dose delivery with multiple static collimation461
Ch. 20Parallel triangulated partitioning for black box optimization487
Ch. 21A case study : composite structure design optimization507
Ch. 22Neural network enhanced optimal self-tuning controller design for induction motors529


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