Nature-Inspired Algorithms and Applied Optimization (Studies in Computational Intelligence #744)
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Fulfillment optionsNature-Inspired Algorithms and Applied Optimization (Studies in Computational Intelligence #744)
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
The book, Nature-Inspired Algorithms and Applied Optimization (Studies in Computational Intelligence #744) [Bulk, Wholesale, Quantity] ISBN#9783319884653 in Paperback by may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
- Publisher
- Springer International Publishing
- Format
- Paperback
- Published
- Aug 15, 2018
- ISBN-13
- 9783319884653
- Pages
- 330
- Printing
- Printed on demand
Nature-Inspired Algorithms and Applied Optimization (Studies in Computational Intelligence #744) for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $175.99 | 12% off list |
| 50 – 99 | $173.99 | 13% off list |
| 100+ | $171.99 | 14% off list |
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