Authors and affiliations
Accessibility informationPDF accessibility summaryThis PDF does Not fully comply with PDF/UA standards but does include limited screen reader support, descriptions for Non-text content (such as images and graphs), bookmarks for easy navigation, and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognise the importance of accessibility and welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibilityThis EPUB is designed with accessibility in mind, aiming to meet the EPUB Accessibility 1.0 AA and WCAG 2.2 Level standards. Its features include Alternative Text description for images and other Non-text content, screen reader-friendly navigation and accessible math. Math is represented either as MathML, LaTeX or in images. If math is represented as image, Alt Text might Not be present. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us via https://www.springernature.com/gp/info/accessibility
Bibliographic informationBook titleMetaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis AuthorsErik Cuevas, Alberto Luque, Bernardo Morales Castañeda, Beatriz Rivera PublisherSpringer Cham Copyright informationThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 Hardcover ISBN978-3-031-63052-1Published: 27 June 2024 Softcover ISBN978-3-031-63055-2Published: 28 June 2025 eBook ISBN978-3-031-63053-8Published: 26 June 2024 Series ISSN1860-949X Series E-ISSN1860-9503 Edition number1 Number of pagesXV, 297 Number of illustrations44 b/w illustrations, 39 illustrations in colour
Keywords
| 
20
Need help with this paper: https://doi.org/10.1007/s10143-025-03818-1
