Multicriteria Decision-Making Analysis for Civil Engineering Applications

Decision-making is a key factor to achieve success in any discipline, especially in a field like civil engineering, which is based on calculations and requires large amounts of information being taken into account. Most processes and procedures are a compendium of many different tasks and requirements specific to each project under development, and making decisions in such environments can often be an arduous endeavor. That is why the need for analytical criteria capable of assisting with untangling complex scenarios has arisen preponderantly. As an all-encompassing resource, Multicriteria Decision-Making Analysis for Civil Engineering Applications facilitates civil engineers by outlining state-of-the-art techniques for quantitative decision-making to optimally select the appropriate approach when faced with operational issues or to prioritize among multiple options. Authored by recognized experts in the field, this book proves to be a balanced reference volume that is essential not just for civil engineers, but also for a wide variety of audiences in interconnected disciplines. - Presents a systematic framework of methodological solutions helping readers to make decisions quickly and accurately - Features several real-life case studies that support understanding and provide reliable actionable guidance - Includes the theoretical underpinnings of decision support tools and emphasizes multicriteria decision analysis techniques applied to civil engineering projects - Offers civil engineers a structured approach to tackle complex decisions and establish priorities in their projects - Is accompanied by an online companion site that includes Excel worksheets, demonstrating step-by-step processes, numerical simulations, and worked-out examples

Prof. Hossein Bonakdari obtained his PhD in civil engineering from the University of Caen Normandy, France. He has worked for several organizations, most recently as Professor at the Department of Civil Engineering, 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 artificial intelligence. 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.