Bioinspired Heuristics for Optimization de El-Ghazali Talbi

Bioinspired Heuristics for Optimization: Studies in Computational Intelligence, cartea 774

El-Ghazali Talbi

Amir Nakib

This book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some properties of intrinsic parallelization, and can be used for various optimizations problems. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software. It is a valuable resource for research academics and industrial practitioners.

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	Preț	Express
Paperback (1)	633^.72 lei 6-8 săpt.
Springer International Publishing – 22 dec 2018	633^.72 lei 6-8 săpt.
Hardback (1)	639^.99 lei 6-8 săpt.
Springer International Publishing – 29 aug 2018	639^.99 lei 6-8 săpt.

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Express

Paperback (1)

633^.72 lei 6-8 săpt.

Springer International Publishing – 22 dec 2018

633^.72 lei 6-8 săpt.

Hardback (1)

639^.99 lei 6-8 săpt.

Springer International Publishing – 29 aug 2018

639^.99 lei 6-8 săpt.

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Specificații

ISBN-13: 9783319951034
ISBN-10: 3319951033
Pagini: 299
Ilustrații: VIII, 314 p. 97 illus., 52 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.63 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Possibilistic Framework for Multi-objective Optimization under Uncertainty.- Solving the Uncapacitated Single Allocation p-Hub Median Problem on GPU. Phase Equilibrium Description of a Supercritical Extraction System using Metaheuristic Optimization Algorithms.- Intrusion Detection System based on a behavioral approach.- A new hybrid method to solve the multi-objective optimization problem for a composite hat-stiffened panel.- Storage yard management: modelling and solving.- Multi-capacitated location problem : A new resolution method combining exact and heuristic approaches based on set partitioning.- Application of genetic algorithm for solving bilevel linear programming problems.- Adapted Bin-Packing algorithm for the yard optimization problem.- Hidden Markov Model classiﬁer for the adaptive ACS-TSP pheromone parameters.

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