Overview
- Addresses recent challenges in optimization methods and techniques associated with the exponential growth in data production
- Gathers the Proceedings of the International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019), held in Balasore, India, on December 19–20, 2019
- Demonstrates how to derive optimal solutions for data-driven problems
Part of the book series: Learning and Analytics in Intelligent Systems (LAIS, volume 10)
Included in the following conference series:
Conference proceedings info: BITMDM 2019.
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About this book
This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.
This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.
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Keywords
- Bio-Inspired Algorithms
- Ant Colony Optimization
- Genetic Algorithm
- Evolutionary Algorithm
- Particle Swarm Optimization
- Game Theory
- Optimization Methods and Techniques
- Fuzzy and Stochastic Optimization
- Multiple Criteria Decision Making
- Multi-Objective Optimization
- Molecular Computing
- Biological Computing
- Swarm Intelligence
- Autonomy-Oriented Computing
- BITMDM
- BITMDS2019
Table of contents (23 papers)
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Biologically Inspired Techniques and Their Applications
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Multi-Criteria Decision Making Approaches
Other volumes
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Biologically Inspired Techniques in Many-Criteria Decision Making
Editors and Affiliations
Bibliographic Information
Book Title: Biologically Inspired Techniques in Many-Criteria Decision Making
Book Subtitle: International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019)
Editors: Satchidananda Dehuri, Bhabani Shankar Prasad Mishra, Pradeep Kumar Mallick, Sung-Bae Cho, Margarita N. Favorskaya
Series Title: Learning and Analytics in Intelligent Systems
DOI: https://doi.org/10.1007/978-3-030-39033-4
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-39032-7Published: 22 January 2020
Softcover ISBN: 978-3-030-39035-8Published: 22 January 2021
eBook ISBN: 978-3-030-39033-4Published: 21 January 2020
Series ISSN: 2662-3447
Series E-ISSN: 2662-3455
Edition Number: 1
Number of Pages: XV, 258
Number of Illustrations: 32 b/w illustrations, 65 illustrations in colour
Topics: Computational Intelligence, Data Engineering, Artificial Intelligence