Evolutionary Algorithms and Agricultural Systems - The Springer International Series in Engineering and Computer Science 647 (Paperback)David G. Mayer (author)
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Agricultural applications using alternate optimization techniques (gradient and direct-search methods, simulated annealing and quenching, and the tabu search strategy) are also listed and discussed. The particular problems and methodologies of these algorithms, including advantageous features that may benefit a hybrid approach or be usefully incorporated into evolutionary algorithms, are outlined. From consideration of this and the published examples, it is concluded that evolutionary algorithms are the superior method for the practical optimization of models of agricultural and natural systems. General recommendations on robust options and parameter settings for evolutionary algorithms are given for use in future studies.
Evolutionary Algorithms and Agricultural Systems will prove useful to practitioners and researchers applying these methods to the optimization of agricultural or natural systems, and would also be suited as a text for systems management, applied modeling, or operations research.
Publisher: Springer-Verlag New York Inc.
Number of pages: 107
Weight: 195 g
Dimensions: 235 x 155 x 6 mm
Edition: Softcover reprint of the original 1st ed. 200