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Min-Rong Chen | Akateeminen Kirjakauppa

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Extremal Optimization - Fundamentals, Algorithms, and Applications
Yong-Zai Lu; Yu-Wang Chen; Min-Rong Chen; Peng Chen; Guo-Qiang Zeng
Taylor & Francis Inc (2016)
Kovakantinen kirja
207,40
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Extremal Optimization - Fundamentals, Algorithms, and Applications
Yong-Zai Lu; Yu-Wang Chen; Min-Rong Chen; Peng Chen; Guo-Qiang Zeng
Taylor & Francis Ltd (2020)
Pehmeäkantinen kirja
59,40
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ostoskoriin kpl
Siirry koriin
Generalized Synchronization And Generalized Consensus Of System Arrays
Lequan Min; Guanrong Chen
World Scientific Publishing Co Pte Ltd (2020)
Kovakantinen kirja
96,00
Tuotetta lisätty
ostoskoriin kpl
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Cloud Computing - 5th International Conference, CloudComp 2014, Guilin, China, October 19-21, 2014, Revised Selected Papers
Victor C.M. Leung; Roy Xiaorong Lai; Min Chen; Jiafu Wan
Springer International Publishing AG (2015)
Pehmeäkantinen kirja
47,70
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Extremal Optimization - Fundamentals, Algorithms, and Applications
207,40 €
Taylor & Francis Inc
Sivumäärä: 334 sivua
Asu: Kovakantinen kirja
Julkaisuvuosi: 2016, 09.03.2016 (lisätietoa)
Kieli: Englanti
Extremal Optimization: Fundamentals, Algorithms, and Applications introduces state-of-the-art extremal optimization (EO) and modified EO (MEO) solutions from fundamentals, methodologies, and algorithms to applications based on numerous classic publications and the authors’ recent original research results. It promotes the movement of EO from academic study to practical applications. The book covers four aspects, beginning with a general review of real-world optimization problems and popular solutions with a focus on computational complexity, such as "NP-hard" and the "phase transitions" occurring on the search landscape.

Next, it introduces computational extremal dynamics and its applications in EO from principles, mechanisms, and algorithms to the experiments on some benchmark problems such as TSP, spin glass, Max-SAT (maximum satisfiability), and graph partition. It then presents studies on the fundamental features of search dynamics and mechanisms in EO with a focus on self-organized optimization, evolutionary probability distribution, and structure features (e.g., backbones), which are based on the authors’ recent research results. Finally, it discusses applications of EO and MEO in multiobjective optimization, systems modeling, intelligent control, and production scheduling.

The authors present the advanced features of EO in solving NP-hard problems through problem formulation, algorithms, and simulation studies on popular benchmarks and industrial applications. They also focus on the development of MEO and its applications. This book can be used as a reference for graduate students, research developers, and practical engineers who work on developing optimization solutions for those complex systems with hardness that cannot be solved with mathematical optimization or other computational intelligence, such as evolutionary computations.

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