Evolutionary Algorithms For Solving Multiobjective Problems

 Evolutionary Algorithms for Solving Multi-Objective Problems(Repost)

"Evolutionary Algorithms for Solving Multi-Objective Problems" (Genetic and Evolutionary Computation)
by Carlos A. Coello Coello, Gary B. Lamont, David A. Van Veldhuizen

Publisher: Springer | Publication Date:2007-09-18 | ISBN:0387332545 | 800 Pages | PDF | 9 MB

Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems.
Evolutionary Algorithms for Solving Multi-Objective Problems by Carlos Coello Coello [Repost]

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) by Carlos Coello Coello
English | Sep 18, 2007 | ISBN: 0387332545 | 810 Pages | PDF | 10 MB

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom.
Carlos A. Coello Coello, "Evolutionary Algorithms for Solving Multi-Objective Problems"(repost)

Carlos A. Coello Coello, "Evolutionary Algorithms for Solving Multi-Objective Problems"
ISBN: 0387332545 | edition 2007 | PDF | 810 pages | 10 mb

Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely applicable in solving both single-objective and multi-objective problems.
Application of Evolutionary Algorithms for Multi-Objective Optimization in VLSI and Embedded Systems (Repost)

Application of Evolutionary Algorithms for Multi-Objective Optimization in VLSI and Embedded Systems By M. C. Bhuvaneswari
2015 | 188 Pages | ISBN: 8132219570 | PDF | 3 MB

Genetic Algorithms for Applied CAD Problems [Repost]  

Posted by tanas.olesya at Feb. 17, 2016
Genetic Algorithms for Applied CAD Problems  [Repost]

Genetic Algorithms for Applied CAD Problems by Viktor M. Kureichik
English | 21 July 2009 | ISBN: 3540852808 | 248 Pages | PDF | 2 MB

New perspective technologies of genetic search and evolution simulation represent the kernel of this book. The authors wanted to show how these technologies are used for practical problems solution.

Evolutionary Algorithms for Mobile Ad Hoc Networks  

Posted by nebulae at Jan. 24, 2016
Evolutionary Algorithms for Mobile Ad Hoc Networks

Bernabé Dorronsoro, "Evolutionary Algorithms for Mobile Ad Hoc Networks"
English | ISBN: 1118341139 | 2015 | 240 pages | PDF | 5 MB
Variants of Evolutionary Algorithms for Real-World Applications (Repost)

Variants of Evolutionary Algorithms for Real-World Applications By Raymond Chiong, Thomas Weise, Zbigniew Michalewicz
2012 | 469 Pages | ISBN: 3642234232 | PDF | 10 MB
Variants of Evolutionary Algorithms for Real-World Applications (Repost)

Variants of Evolutionary Algorithms for Real-World Applications By Raymond Chiong, Thomas Weise, Zbigniew Michalewicz
2012 | 469 Pages | ISBN: 3642234232 | PDF | 10 MB
Variants of Evolutionary Algorithms for Real-World Applications (Repost)

Variants of Evolutionary Algorithms for Real-World Applications By Raymond Chiong, Thomas Weise, Zbigniew Michalewicz
2012 | 469 Pages | ISBN: 3642234232 | PDF | 11 MB
Application of Evolutionary Algorithms for Multi-objective Optimization by M.C. Bhuvaneswari [Repost]

Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems by M.C. Bhuvaneswari
English | Aug 20, 2014 | ISBN: 8132219570 | 181 Pages | PDF | 2 MB

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.