AAP Research Notes on Optimization and Decision Making Theories


About the Series

Series Editors:

Dr. Prasenjit Chatterjee
Department of Mechanical Engineering, MCKV Institute of Engineering, Howrah - 711204, West Bengal, India
E-Mail: dr.prasenjitchatterjee6@gmail.com / prasenjit2007@gmail.com

Dr. Dragan Pamucar
University of Defence, Military academy, Department of logistics, Belgrade, Pavla Juriši?a Šturma 33, 11000 Belgrade, Serbia
E-Mail: dpamucar@gmail.com

Dr. Morteza Yazdani
Department of Business & Management, Universidad Loyola Andalucia, Seville- 141014, Spain
E-Mail: morteza_yazdani21@yahoo.com

Dr. Anjali Awasthi
Associate Professor and Graduate Program Director (M.Eng.), Concordia Institute for Information Systems Engineering, Concordia, Canada- H3G 2W1
E-Mail: anjali.awasthi@concordia.ca


Brief description about the series:

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A solution that is better with respect to one objective may be a compromising one for other objectives. This compels one to choose a solution that is optimal with respect to only one objective. Due to such constraints, multi-objective optimization problems (MOPs) are difficult to solve since the objectives usually conflict with each other. It is usually hard to find an optimal solution that satisfies all objectives from the mathematical point of view. In addition, it is quite common that the criteria of real-world MOPs encompass uncertain information, which becomes quite a challenging task for a decision maker to select the criteria. Also, the complexities involved in designing mathematical models increase. Considering, planning, and appropriate decision-making require the use of analytical methods that examine trade-offs; consider multiple scientific, political, economic, ecological, and social dimensions; and reduce possible conflicts in an optimizing framework. Among all these, real-world multi-criteria decision-making (MCDM) problems related to engineering optimizations are categorically important and are quite often encountered with a wide range of applicability.

MCDM problems are basically a fundamental issue in various fields, including applied mathematics, computer science, engineering, management, and operations research. MCDM models provide a useful way for modeling various real-world problems and are extensively used in many different types of systems, including, but not limited to, communications, mechanics, electronics, manufacturing, business management, logistics, supply chain, energy, urban development, waste management, and so forth.

In the aforementioned cases, modeling of multiple criteria problems often becomes more complex if the associated parameters are uncertain and imprecise in nature. Impreciseness or uncertainty exists within the parameters due to imperfect knowledge of information, measurement uncertainty, sampling uncertainty, mathematical modeling uncertainty, etc. Theories like probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, grey theory, neutrosophic uncertainty theory available in the existing literature deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems are not explored in depth, and a lot can be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed on various uncertain frameworks with special emphasis on sustainability, manufacturing, communications, biomedical, electronics, materials, energy, agriculture, environmental engineering, strategic management, flood risk management, supply chain, waste management, transportations, economics, and industrial engineering problems, to name a few.


Coverage & Approach:
The primary endeavor of this series is to introduce and explore contemporary research developments in a variety of rapidly growing decision-making areas. The volumes will deal with the following topics:

  • Crisp MCDM models
  • Rough set theory in MCDM
  • Fuzzy MCDM
  • Neutrosophic MCDM models
  • Grey set theory
  • Mathematical programming in MCDM
  • Big data in MCDM
  • Soft computing techniques
  • Modelling in engineering applications
  • Modeling in economic issues
  • Waste management
  • Agricultural practice
  • Material selection
  • Renewable energy planning
  • Industry 4.0
  • Sustainability
  • Supply chain management
  • Environmental policies
  • Manufacturing processes planning
  • Transportation and logistics
  • Strategic management
  • Natural resource management
  • Biomedical applications
  • Future studies and technology foresight
  • MCDM in governance and planning
  • MCDM and social issues
  • MCDM in flood risk management
  • New trends in multi-criteria evaluation
  • Multi-criteria analysis in circular economy
  • Multi-criteria evaluation for urban and regional planning
  • Integrated MCDM approaches for modeling relevant applications and real-life problems


Types of volumes:
This series reports on current trends and advances in optimization and decision-making theories in a wider range of domains for academic and research institutes along with industrial organizations. The series will cover the following types of volumes:
  • Authored volumes
  • Edited volumes
  • Conference proceedings
  • Short research (thesis-based) books
  • Monographs


Features of the volumes will include recent trends, model extensions, developments, real-time examples, case studies, and applications.

The volumes aim to serve as valuable resources for undergraduate, postgraduate and doctoral students, as well as for researchers and professionals working in a wider range of areas.

Book manuscripts should be a minimum 250–500 pages per volume (11 point Times Roman, in Word, 1.5 line spacing).

Applications of Artificial Intelligence in Business and Finance
Applications of Artificial Intelligence in Business and Finance
Editors: Vikas Garg, PhD, Shalini Aggarwal, PhD, Pooja Tiwari, PhD, Prasenjit Chatterjee, PhD
Multi-Criteria Decision-Making Techniques in Waste Management
Multi-Criteria Decision-Making Techniques in Waste Management
Authors: Suchismita Satapathy, PhD, Debesh Mishra, and Prasanjit Chatterjee, PhD
Advances in Data Science and Computing Technology
Advances in Data Science and Computing Technology
Editors: Suman Ghosal, Amitava Choudhury, Vikram Kr. Saxena, Arindam Biswas, and Prasenjit Chatterjee
Advanced Computer Science Applications
Advanced Computer Science Applications
Editors: Karan Singh, PhD, Latha Banda, PhD and Manisha Manjul, PhD
Decision-Making Models and Applications in Manufacturing Environments
Decision-Making Models and Applications in Manufacturing Environments
Editors: Pushpdant Jain, PhD, Kumar Abhishek, and Prasenjit Chatterjee, PhD
Precision Agriculture for Sustainability
Precision Agriculture for Sustainability
Editors: Narendra Khatri, PhD, Ajay Kumar Vyas, PhD, Celestine Iwendi, PhD, and Prasenjit Chatterjee, PhD
Multimedia Security
Multimedia Security
Editors: Bhaskar Mondal, PhD, and Shyam Singh Rajput, PhD
Computational Optimization, Modeling, and Simulation for Engineering Applications
Computational Optimization, Modeling, and Simulation for Engineering Applications
Editors: Anupam Shukla, PhD, Sourabh Rungta, PhD, Mohan Awasthy, PhD, and Rakesh L. Himte, PhD
Advances in Intelligent Systems
Advances in Intelligent Systems
Editors: Manisha Guduri, PhD, Uma Maheswari V, PhD, Rajanikanth Aluvalu, PhD, and Amit Krishna Dwivedi, PhD
Attacks on Artificial Intelligence
Attacks on Artificial Intelligence
Editors: Kukatlapalli Pradeep Kumar, PhD, Boppuru Rudra, PhD, Vinay Jha Pillai, PhD, and Prasenjit Chatterjee, PhD
 Sustainable Development
Sustainable Development
Editors: Qazi Mazhar Ali, PhD, Rizwan Ahmad, PhD, Irfan Ali, PhD, and Prasenjit Chatterjee, PhD



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