Numerical Optimization and Algorithms | 2nd Edition

ISBN 10: 3725873585 / ISBN 13: 9783725873586

Published by MDPI AG, 2026

About this Item

Numerical Optimization and Algorithms | 2nd Edition | Buch | Englisch | 2026 | MDPI AG | EAN 9783725873586 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

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Bibliographic Details

• Title: Numerical Optimization and Algorithms | 2nd Edition
• Publisher: MDPI AG
• Publication Date: 2026
• Language: English
• ISBN 10: 3725873585
• ISBN 13: 9783725873586
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 30D millimeters 250 millimeters width by 175 millimeters height by 30 millimeters depth
• Weight: 1179 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The Special Issue "Numerical Optimization and Algorithms (3rd Edition)", hosted by the MDPI journal Algorithms, provides a crucial forum for the latest advancements in computational mathematics. As science and engineering problems grow increasingly complex, this edition focuses on the urgent need for robust solvers capable of navigating high-dimensional and nonlinear landscapes. The scope of the Special Issue encompasses a broad range of scientific fields, including physics, data science, economics, and biology. It specifically addresses modern challenges like the "curse of dimensionality," uncertainty in modeling, and the integration of data science with traditional numerical methods. Key areas of interest include the following: Graph Theory and Algebra: Developing fundamental structures for modern computing; Linear and Nonlinear Programming: Refining optimization under complex constraints; Stochastic Modeling: Handling the inherent unpredictability in real-world data; Differential Equations: Advancing numerical solvers for mechanical and environmental systems. Led by Guest Editors Prof. Dr. Dunhui Xiao and Prof. Dr. Shuai Li, this collection highlights the shift from purely theoretical algorithms to scalable, practical solutions. By fostering multidisciplinary collaboration, the Special Issue aims to promote innovative techniques-from metaheuristics to AI-driven optimization-that empower researchers to solve high-stakes problems in global logistics, finance, and industrial automation more efficiently.