Nature-inspired methods for stochastic, robust and dynamic optimization / / Javier Del Ser, Eneko Osaba, editors.
Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in h...
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| Place / Publishing House: | [Place of publication not identified] : : IntechOpen,, [2018] ©2018 |
| Year of Publication: | 2018 |
| Language: | English |
| Physical Description: | 1 online resource (70 pages) :; illustrations |
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| 100 | 1 | |a Del Ser, Javier |4 edt | |
| 245 | 0 | 0 | |a Nature-inspired methods for stochastic, robust and dynamic optimization / |c Javier Del Ser, Eneko Osaba, editors. |
| 260 | |b IntechOpen |c 2018 | ||
| 264 | 1 | |a [Place of publication not identified] : |b IntechOpen, |c [2018] | |
| 264 | 4 | |c ©2018 | |
| 300 | |a 1 online resource (70 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | |a Description based on: online resource; title from PDF information screen (InTech, viewed October 21, 2022). | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems. | ||
| 546 | |a English | ||
| 650 | 0 | |a Algorithms. | |
| 650 | 0 | |a Logic design. | |
| 653 | |a Optimization | ||
| 776 | |z 1-78923-328-3 | ||
| 700 | 1 | |a Del Ser, Javier, |e editor. | |
| 700 | 1 | |a Osaba, Eneko, |e editor. | |
| 906 | |a BOOK | ||
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