Biologically Inspired Techniques in Many-Criteria Decision Making : International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019) /

Biologically Inspired Techniques in Many-Criteria Decision Making : International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019) /

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Bibliographic Details
Meeting name:	International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (2019)
Imprint:	Cham : Springer, 2020.
Description:	1 online resource (xv, 258 p.) : ill. (some col.)
Language:	English
Series:	Learning and Analytics in Intelligent Systems ; v. 10 Learning and Analytics in Intelligent Systems ; v. 10.
Subject:	Multiple criteria decision making -- Congresses. Natural computation -- Congresses. Multiple criteria decision making. Natural computation. Conference papers and proceedings.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12603331

Hidden Bibliographic Details
Varying Form of Title:	BITMDM 2019
Other authors / contributors:	Dehuri, Satchidananda. Mishra, Bhabani Shankar Prasad. Mallick, Pradeep Kumar, 1984- Cho, Sung-Bae. Favorskaya, Margarita N.
ISBN:	9783030390334 3030390330 9783030390327
Notes:	Includes author index.
Summary:	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.
Standard no.:	10.1007/978-3-030-39 10.1007/978-3-030-39033-4