Complexity

Managing Information Uncertainty and Complexity in Decision-Making


Status
Published

1Vilnius Gediminas Technical University, Vilnius, Lithuania

2La Salle University, Philadelphia, USA

3Universiti Teknologi Malaysia, Johor, Malaysia


Managing Information Uncertainty and Complexity in Decision-Making

Description

Information uncertainty and complexity is a common paradigm in modern decision making because perfect information is seldom available to decision makers. A wide range of statistical and nonstatistical decision-making models have been proposed in the literature to model complex systems under uncertainty. Statistical methods (i.e., probability theory) are useful in modeling complex systems with incomplete or inaccurate data while nonstatistical methods (i.e., fuzzy set theory, rough set theory, possibility theory, or fuzzy neural networks) are useful for modeling complex systems with imprecise, ambiguous, or vague data.

Today’s real-world problems involve multiple data sets, some precise or objective and some uncertain or subjective. Hybrid decision-making models are quickly emerging as alternative methods of choice for modeling complex systems under uncertainty. Managing uncertainty is a prerequisite to effective problem solving and decision-making in complex systems.

We invite authors to submit original research articles that propose formal decision-making methods to both describe and rationalize the process of decision making in complex systems under uncertainty. This special issue covers managing information uncertainty in complex systems by means of the following topics.

Potential topics include but are not limited to the following:

  • Statistical methods such as probabilistic approaches and simulation-based methods
  • Nonstatistical methods such as fuzzy set theory, rough set theory, possibility theory, or fuzzy neural networks
  • Hybrid multiple-criteria decision-making methods using interval-valued fuzzy sets, intuitionistic fuzzy sets, or neutrosophic sets

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 1268980
  • - Editorial

Managing Information Uncertainty and Complexity in Decision-Making

Jurgita Antucheviciene | Madjid Tavana | ... | Romualdas Bausys
  • Special Issue
  • - Volume 2017
  • - Article ID 1608147
  • - Review Article

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

Abbas Mardani | Mehrbakhsh Nilashi | ... | Othman Ibrahim
  • Special Issue
  • - Volume 2017
  • - Article ID 3759514
  • - Research Article

An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning

Néstor Rodríguez-Padial | Marta Marín | Rosario Domingo
  • Special Issue
  • - Volume 2017
  • - Article ID 9546272
  • - Research Article

Managing Information Uncertainty in Wave Height Modeling for the Offshore Structural Analysis through Random Set

Keqin Yan | Yi Zhang | ... | Akhil Garg
  • Special Issue
  • - Volume 2017
  • - Article ID 5937376
  • - Research Article

Some Generalized Pythagorean Fuzzy Bonferroni Mean Aggregation Operators with Their Application to Multiattribute Group Decision-Making

Runtong Zhang | Jun Wang | ... | Ming Yu
  • Special Issue
  • - Volume 2017
  • - Article ID 9712626
  • - Research Article

Implications for Firms with Limited Information to Take Advantage of Reference Price Effect in Competitive Settings

Junhai Ma | Zhanbing Guo
  • Special Issue
  • - Volume 2017
  • - Article ID 4359195
  • - Research Article

An Improved Belief Entropy and Its Application in Decision-Making

Deyun Zhou | Yongchuan Tang | Wen Jiang
Complexity
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 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
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