Biologically Inspired Techniques in Many-Criteria Decision Making

Biologically Inspired Techniques in Many-Criteria Decision Making

  • Satchidananda Dehuri
  • Bhabani Shankar Prasad Mishra
  • Pradeep Kumar Mallick
  • Sung-Bae Cho
  • Margarita N. Favorskaya
Publisher:Springer NatureISBN 13: 9783030390334ISBN 10: 3030390330

Paperback & Hardcover deals ―

Amazon IndiaGOFlipkart GOSnapdealGOSapnaOnlineGOJain Book AgencyGOBooks Wagon₹15,866Book ChorGOCrosswordGODC BooksGO

e-book & Audiobook deals ―

Amazon India GOGoogle Play Books ₹167.2Audible GO

* Price may vary from time to time.

* GO = We're not able to fetch the price (please check manually visiting the website).

Know about the book -

Biologically Inspired Techniques in Many-Criteria Decision Making is written by Satchidananda Dehuri and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3030390330 (ISBN 10) and 9783030390334 (ISBN 13).

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.