Titlebook: Adaptive Differential Evolution; A Robust Approach to Jingqiao Zhang,Arthur C. Sanderson Book 2009 Springer-Verlag Berlin Heidelberg 2009 E

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Adaptive Differential Evolution978-3-642-01527-4Series ISSN 1867-4534 Series E-ISSN 1867-4542

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Developing Loyalty and Commitment,ficients of a neural network minimize classification errors? What combination of bids maximizes the outcome in an auction? What variable- and check-node distributions optimize a low-density parity-check code design? In general, optimization problems arise wherever such resources as space, time and c

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MORPH

Bad Breaks in Real GDP and Employmentits success in various practical applications, only a few theoretical results [2], [13], [14], [15] have been obtained concerning its stochastic behavior and most of them focus on the mutation and crossover operations while omitting detailed analysis of selection that is immediately related to objec

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Julie A. Chappell,Mallory Young application, the outcome may be directly linked to cost, profit and/or many other inevitably conflicting criteria that have heavy impacts on the overall performance. An air traffic control system is such an example. In flight planning, air traffic controllers need to take into account different per

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Julie A. Chappell,Mallory Younga given time horizon, have been used in various credit decision-making applications. Empirical TPMs calculated from historical data generally do not satisfy desired properties. An alternative method is to formulate the problem into an optimization framework [165], i.e., to find an optimized TPM that