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Numerical Optimization of Computer ModelsJune 1981
Publisher:
  • John Wiley & Sons, Inc.
  • 605 Third Ave. New York, NY
  • United States
ISBN:978-0-471-09988-8
Published:01 June 1981
Pages:
398
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Abstract

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  185. Migdalas A, Toraldo G and Kumar V (2003). Nonlinear optimization and parallel computing, Parallel Computing, 29:4, (375-391), Online publication date: 1-Apr-2003.
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  187. Pierreval H, Caux C, Paris J and Viguier F (2003). Evolutionary approaches to the design and organization of manufacturing systems, Computers and Industrial Engineering, 44:3, (339-364), Online publication date: 1-Mar-2003.
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  189. Berthold M and Hand D References Intelligent data analysis, (475-500)
  190. Ono I, Kita H and Kobayashi S A real-coded genetic algorithm using the unimodal normal distribution crossover Advances in evolutionary computing, (213-237)
  191. Vassilev V, Fogarty T and Miller J Smoothness, ruggedness and neutrality of fitness landscapes Advances in evolutionary computing, (3-44)
  192. Spirov A and Holloway D (2003). Evolutionary techniques for image processing a large dataset of early Drosophila gene expression, EURASIP Journal on Advances in Signal Processing, 2003, (824-833), Online publication date: 1-Jan-2003.
  193. Herrero J, Portas J, de Jesús A, López J, de Miguel Vela G and Corredera J (2003). Application of evolution strategies to the design of tracking filters with a large number of specifications, EURASIP Journal on Advances in Signal Processing, 2003, (766-779), Online publication date: 1-Jan-2003.
  194. Poli R and Cagnoni S (2003). Editorial, EURASIP Journal on Advances in Signal Processing, 2003, (733-739), Online publication date: 1-Jan-2003.
  195. Arnold D and Beyer H (2003). A Comparison of Evolution Strategies with Other Direct Search Methods in the Presence of Noise, Computational Optimization and Applications, 24:1, (135-159), Online publication date: 1-Jan-2003.
  196. Arnold D and Beyer H (2002). Performance analysis of evolution strategies with multi-recombination in high-dimensional R-search spaces disturbed by noise, Theoretical Computer Science, 289:1, (629-647), Online publication date: 23-Oct-2002.
  197. Beyer H, Schwefel H and Wegener I (2002). How to analyse evolutionary algorithms, Theoretical Computer Science, 287:1, (101-130), Online publication date: 25-Sep-2002.
  198. Parsopoulos K and Vrahatis M (2002). Recent approaches to global optimization problems through Particle Swarm Optimization, Natural Computing: an international journal, 1:2-3, (235-306), Online publication date: 1-Jun-2002.
  199. Smith J (2002). On Appropriate Adaptation Levels for the Learning of Gene Linkage, Genetic Programming and Evolvable Machines, 3:2, (129-155), Online publication date: 1-Jun-2002.
  200. Beyer H and Schwefel H (2002). Evolution strategies –A comprehensive introduction, Natural Computing: an international journal, 1:1, (3-52), Online publication date: 1-May-2002.
  201. Fredj E Real Time Interactive Visualization System for Flexible Molecular Docking Proceedings of the 16th International Parallel and Distributed Processing Symposium
  202. Fredj E Real Time Interactive Visualization System for Flexible Molecular Docking Proceedings of the 16th International Parallel and Distributed Processing Symposium
  203. Cortez P, Rocha M and Neves J (2002). A Lamarckian Approach for Neural Network Training, Neural Processing Letters, 15:2, (105-116), Online publication date: 12-Apr-2002.
  204. Tzannetakis N and Van De Peer J (2002). Design optimization through parallel-generated surrogate models, optimization methodologies and the utility of legacy simulation software, Structural and Multidisciplinary Optimization, 23:2, (170-186), Online publication date: 1-Mar-2002.
  205. Berlanga A, Sanchis A, Isasi P and Molina J (2002). Neural Network Controller against Environment, Journal of Intelligent and Robotic Systems, 33:2, (139-166), Online publication date: 1-Feb-2002.
  206. Hamda H, Jouve F, Lutton E, Schoenauer M and Sebag M (2002). Compact Unstructured Representations for Evolutionary Design, Applied Intelligence, 16:2, (139-155), Online publication date: 7-Jan-2002.
  207. Myers R and Hancock E (2001). Empirical Modelling of Genetic Algorithms, Evolutionary Computation, 9:4, (461-493), Online publication date: 1-Dec-2001.
  208. Yang J, Horng J, Lin C and Kao C (2001). Optical Coating Designs Using the Family Competition Evolutionary Algorithm, Evolutionary Computation, 9:4, (421-443), Online publication date: 1-Dec-2001.
  209. Vancorenland P, Van der Plas G, Steyaert M, Gielen G and Sansen W A layout-aware synthesis methodology for RF circuits Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design, (358-362)
  210. Bentley P and Corne D Introduction to creative evolutionary systems Creative evolutionary systems, (1-75)
  211. Cantú-Paz E (2001). Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms, Journal of Heuristics, 7:4, (311-334), Online publication date: 1-Jul-2001.
  212. Hansen N and Ostermeier A (2001). Completely Derandomized Self-Adaptation in Evolution Strategies, Evolutionary Computation, 9:2, (159-195), Online publication date: 1-Jun-2001.
  213. Ilich N and Simonovic S (2001). An Evolution Program for Non-Linear Transportation Problems, Journal of Heuristics, 7:2, (145-168), Online publication date: 1-Mar-2001.
  214. Baum E, Boneh D and Garrett C (2001). Where Genetic Algorithms Excel, Evolutionary Computation, 9:1, (93-124), Online publication date: 1-Jan-2001.
  215. Onbaşoğlu E and Özdamar L (2001). Parallel Simulated Annealing Algorithms in Global Optimization, Journal of Global Optimization, 19:1, (27-50), Online publication date: 1-Jan-2001.
  216. Herrera F and Lozano M (2000). Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes, Applied Intelligence, 13:3, (187-204), Online publication date: 29-Nov-2000.
  217. Hanne T (2000). Global Multiobjective Optimization Using Evolutionary Algorithms, Journal of Heuristics, 6:3, (347-360), Online publication date: 1-Aug-2000.
  218. Miller J, Job D and Vassilev V (2000). Principles in the Evolutionary Design of Digital Circuits—Part II, Genetic Programming and Evolvable Machines, 1:3, (259-288), Online publication date: 1-Jul-2000.
  219. Xu S and Frank T (2000). Forecasting the efficiency of test generation algorithms for combinational circuits, Journal of Computer Science and Technology, 15:4, (326-337), Online publication date: 1-Jul-2000.
  220. ACM
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  223. Tzifa E, Demesticha V, Demestichas P, Theologou M and Anagnostou M (1999). Design of the Access Network Segment of Future Mobile Communications Systems, Wireless Personal Communications: An International Journal, 11:3, (247-268), Online publication date: 1-Dec-1999.
  224. Baumann B and Kost B (1999). Topology Optimization of Trusses—Random Cost Method Versus Evolutionary Algorithms, Computational Optimization and Applications, 14:2, (203-218), Online publication date: 1-Sep-1999.
  225. Chen S, Guerra-Salcedo C and Smith S Non-standard crossover for a standard representation--commonality-based feature subset selection Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation - Volume 1, (129-134)
  226. Rae A and Parameswaran S Application-specific heterogeneous multiprocessor synthesis using differential-evolution Proceedings of the 11th international symposium on System synthesis, (83-88)
  227. Hunter A (1998). Crossing Over Genetic Algorithms, Journal of Heuristics, 4:2, (179-192), Online publication date: 1-Jul-1998.
  228. Fuentes O and Nelson R (1998). Learning Dextrous Manipulation Skills for Multifingered Robot Hands Using the Evolution Strategy, Autonomous Robots, 5:3-4, (395-405), Online publication date: 1-Jul-1998.
  229. Fuentes O and Nelson R (1998). Learning Dextrous Manipulation Skills for MultifingeredRobot Hands Using the Evolution Strategy, Machine Language, 31:1-3, (223-237), Online publication date: 1-Apr-1998.
  230. Sebag M, Schoenauer M and Peyral M (1998). Revisiting the Memory of Evolution, Fundamenta Informaticae, 35:1-4, (125-162), Online publication date: 1-Jan-1998.
  231. Esquivel S, Leiva H and Gallardt R (1998). Selection Mechanisms in Evolutionary Algorithms, Fundamenta Informaticae, 35:1-4, (17-33), Online publication date: 1-Jan-1998.
  232. Yao X Global Optimisation by Evolutionary Algorithms Proceedings of the 2nd AIZU International Symposium on Parallel Algorithms / Architecture Synthesis
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  234. Süß W, Eggert H, Georges-Schleuter M, Jakob W, Meinzer S and Quinte A Simulation and design optimization of microsystems based on standard simulators and adaptive search techniques Proceedings of the conference on European design automation, (322-327)
  235. Larrañaga P, Poza M, Yurramendi Y, Murga R and Kuijpers C (1996). Structure Learning of Bayesian Networks by Genetic Algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 18:9, (912-926), Online publication date: 1-Sep-1996.
  236. Angeline P Evolving fractal movies Proceedings of the 1st annual conference on genetic programming, (503-511)
  237. Angeline P An investigation into the sensitivity of genetic programming to the frequency of leaf selection during subtree crossover Proceedings of the 1st annual conference on genetic programming, (21-29)
  238. ACM
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  239. Hering K, Haupt R and Villmann T Hierarchical strategy of model partitioning for VLSI-design using an improved mixture of experts approach Proceedings of the tenth workshop on Parallel and distributed simulation, (106-113)
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  243. Beyer H (1994). Toward a theory of evolution strategies, Evolutionary Computation, 2:4, (381-407), Online publication date: 1-Dec-1994.
  244. Ostermeier A, Gawelczyk A and Hansen N (1994). A derandomized approach to self-adaptation of evolution strategies, Evolutionary Computation, 2:4, (369-380), Online publication date: 1-Dec-1994.
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  246. ACM
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  247. Beyer H (1993). Toward a theory of evolution strategies, Evolutionary Computation, 1:2, (165-188), Online publication date: 1-Jun-1993.
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Contributors
  • Technical University Dortmund

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