Multi-Criteria Decision-Making Analysis for Civil Engineering Applications

Erscheinungsjahr 2024
ISBN: 978-0-443-22282-5
Verlag: Elsevier Science

Buch, Englisch, 400 Seiten, Format (B × H): 151 mm x 229 mm

Multi-Criteria Decision-Making Analysis for Civil Engineering Applications helps civil engineers by outlining state-of-the-art tactics for quantitative decision-making to optimally select the appropriate approach when faced with operational issues, or to prioritize projects among multiple options. Authored by recognized experts in the field, the volume proves to be a balanced reference book that’s essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. Decision-making is a key factor to achieve success in any discipline, especially in a field which requires handling large amounts of information and is based on calculations as civil engineering. Most processes and procedures are a compendium of many different tasks and requirements of each project under development, also involving a great variety of specific factors and numerical values to be considered. Making decisions in such environments can often be an arduous endeavor, and that is why the need for analytical criteria capable of assisting with untangling complex scenarios has arisen preponderantly.

Autoren/Hrsg.

Bonakdari, Hossein

Noori, Amir

Morovati, Khosro

Fachgebiete

• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Nachhaltige Landwirtschaft
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung
• Technische Wissenschaften Bauingenieurwesen Bauingenieurwesen
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Mathematik | Informatik EDV | Informatik Informatik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik

Inhaltsverzeichnis

1. Overview of Decision-making 2. Introduction of Multi-criteria Decision-making 3. Scoring Methods 4. Compromising Techniques 5. Pair-wise Comparison Techniques 6. Outranking Methods 7. Fuzzy Multi-criteria Decision-making 8. Group Decision-making 9. Integrated Multi-criteria Decision-making Methods 10. AI Algorithms and Multi-criteria Decision-making 11. Multi-criteria Decision-making Analysis in Microsoft Excel

Über Autor(innen)

Morovati, Khosro
Dr. Morovati obtained his PhD in Hydraulic Engineering from Tsinghua University (China). His recent works are dedicated to finding nature-based scientific solutions for transboundary rivers and water resource management by developing hydrological, hydrodynamic, data science, and multi-criteria decision-making approaches. His study also looks at the impacts produced by climate variation and human activities on flow regime shifts of rivers and lakes. He has published several papers in high-quality journals.

Noori, Amir
Amir Noori is a PhD candidate at the Department of Civil Engineering of the University of Ottawa (Canada). He received his MSc in Water Resource Engineering and Management from Razi University (Iran). His research interests are directed at water resources planning, integrated multi-criteria decision-making models, and GIS and RS applications. He developed different novel multi-criteria decision-making techniques to address several practical challenges, which were published in high-impact factor journals. Based on his excellent resume, the University of Ottawa secured him an admission scholarship and he was nominated for the merit scholarship as well.

Bonakdari, Hossein
Dr. Bonakdari obtained his PhD in Civil Engineering from the University of Caen Normandy (France). He has worked for several organizations and most recently as an Associate Professor at the Department of Civil Engineering of the University of Ottawa (Canada). He is one of the most influential scientists in the field of developing novel algorithms for solving practical problems through the decision-making abilities of AI. His research also focuses on creating comprehensive methodologies in the areas of simulation modeling, optimization, and machine learning algorithms. The results obtained from his research have been published in international journals and presented at international conferences. He was included in the list of the world's top 2% scientists, published by Stanford University, and is on the Editorial board of several journals.