You can attend a workshop regardless of whether you register for the entire conference or not. In either case you need to click on the registration link, select the workshops that you want to attend and make the required payment. Registration to the workshops can be done either along with the registration to the conference or in a different time and it will also be available on site. The schedule is in Eastern Standard Time, EST (GMT-5).
You can find details for the workshops registration here: REGISTRATION Thursday 12 December, 2024
8:00 am - 9:00 am
Mastering AHP Models in Python: Setup, Calculation, and Sensitivity Analysis with AhpAnpLib (Lirong Wei)
9:00 am - 10:00 am
Introduction to ANP (Ilker Topcu)
10:00 am - 11:00 am
Advancing with ANP. The use of ratings and BOCR models (Monica Garcia Melon)
11:00 am - 12:00 pm
Data Analytics in ANP with Python: Unveiling Insights through the Supermatrix (Elena Rokou)
12:00 pm - 1:00 pm
The Absolute Measurement in AHP/ANP: The Rating Mode and its Need for Thresholds (Claudio Garuti)
Mastering AHP Models in Python: Setup, Calculation, and Sensitivity Analysis with AhpAnpLib
Lirong Wei This workshop will guide participants through setting up the Python AhpAnpLib library in Google Colab. Participants will learn how to structure AHP models using Excel and repurpose SuperDecisions models by importing them into Python. The session emphasizes environment setup and the creation of AHP models using the Python library.
Requirements:
Software: No software installation required; Google Colab will be used.
Previous Knowledge: A basic understanding of AHP models is required. No prior Python knowledge is needed for this workshop.
Short Bio
Lirong Wei is a senior data analyst, BI developer, and researcher with a PhD in Management Science and Engineering from the University of Science and Technology Beijing, and a master's degree in Statistics from the University of Pittsburgh. Lirong has served as a visiting scholar at the Katz Business School at the University of Pittsburgh, where they collaborated with Dr. Thomas Saaty, co-authoring the book "Complete Structural Functions and Connections of the Nervous System." Lirong works on interdisciplinary research projects in big data, AI, and decision-making models, and collaborates with the Creative Decisions Foundation (CDF) to promote AHP methodologies globally.
Introduction to ANP
Ilker Topcu Analytic Network Process (ANP) is one of the most powerful methodologies for combining and evaluating judgments of the decision-makers to effectively rank alternatives, choose a compromise solution, and predict outcomes. ANP, developed by Thomas L. Saaty, is a widely used technique for structuring, modeling, and analyzing complex decisions based on mathematics and psychology.
Decision-makers are poor at assimilating large quantities of information on their problems. They cope with cognitive overload by employing heuristics that simplify the problem. This can lead to the selection of suboptimal alternatives. Participants in the workshop will carry out an experiment on cognitive psychology and learn Miller’s “the magical number seven, plus or minus two: some limits on our capacity for processing information”.
In complex decisions, there may be dependence and feedback. We will discuss how network modelling improves the priorities derived from judgments and makes predictions much more accurate.
We will go through the arrangement of paired comparison judgements in a matrix, the calculation of eigenvector and inconsistency of the pairwise comparison matrix, and then, the formation of the supermatrix, weighted supermatrix, and limiting supermatrix. Last but not least, we will examine Saaty’s Compatibility Index.
Short Bio
Y. Ilker Topcu is a Professor of Decision Sciences at Industrial Engineering Department of Istanbul Technical University (ITU). He visited Leeds University Business School from 1998 through 1999 as a visiting researcher and received his Ph.D. degree in Engineering Management from ITU in 2000.
Advancing with ANP. The use of ratings and BOCR models
Monica Garcia Melon This workshop will cover advanced techniques in the application of Analytic Network Process (ANP) models for decision-making. The session is structured in two parts. The first part will focus on the use of the Benefits, Opportunities, Costs, and Risks (BOCR) models. In the second part, we will explore how to assess alternatives using the ratings method in case we want to avoid pairwise comparisons.
Requirements:
Participants should have a basic understanding of ANP or have attended the previous introductory ANP workshop.
Short Bio
Monica Garcia Melon is a distinguished professor and researcher in the field of decision analysis and multi-criteria decision-making (MCDM). She is widely recognized for her expertise in applying the AHP/ANP and other decision-making methodologies to a wide range of fields, including engineering, management, and sustainability. As a faculty member at the Universitat Politècnica de València in Spain, Monica has made significant contributions to academic research, published numerous papers in international journals, and played a pivotal role in advancing the field of decision science. She is also actively involved in the global community of AHP and MCDM researchers and practitioners, frequently contributing to international conferences and workshops. Monica’s work continues to have a strong impact on both academic and professional practices in decision-making.
Data Analytics in ANP with Python: Unveiling Insights through the Supermatrix
Elena Rokou Subtitle: Mastering the Supermatrix and Sensitivity Analysis with AhpAnpLib for Strategic Decision-Making
In this 45-minute hands-on workshop, participants will explore data analytics within the ANP framework using the AhpAnpLib Python library. Focusing on the supermatrix as a core tool for understanding interdependencies between criteria, we will walk through a real-world market share model. You'll learn how to calculate and interpret the supermatrix, use sensitivity analysis to test decision robustness and extract strategic insights that can be applied in consulting and AI-enhanced decision-making. This workshop is ideal for professionals seeking to deepen their data-driven decision-making skills using Python and ANP.
Participants will leave with the ability to:
Set up and analyze an ANP market share model using AhpAnpLib. Conduct sensitivity analysis to explore how changes in criteria weights affect outcomes. Leverage AI-driven data analytics to enhance the interpretation of ANP results. Apply insights gained from ANP models to real-world consulting scenarios.
Requirements:
Software: Google Colab (no installation required). Prior Knowledge: Familiarity with ANP models. No Python experience is required.
Short Bio
Dr Elena Rokou is the Chief Research Officer at Creative Decisions Foundation, the AHP/ANP research institute funded by Dr Thomas Saaty. She holds a PhD degree in the field of operational research, focusing on project scheduling and evolutionary algorithms from the National Technical University of Athens, Mechanical Engineering School, Sector of Industrial Management and Operational Research, a MSc in Management Engineering and a Software Engineering Diploma. Her main research interests cover project scheduling, optimization, evolutionary algorithms, MCDA and decision support tools.
Since 2020, Dr. Rokou has served as an Adjunct Professor at the University of Pittsburgh’s Katz Graduate School of Business. In 2024, she was honored with both the Full-Time Masters Student Choice Award for Outstanding Teacher and the Executive MBA Student Choice Award for Outstanding Faculty of the Year from the Katz Graduate School of Business. Additionally, she is a Fellow of the International Center for Conflict Resolution (IC4CR), where she continues to contribute her expertise to the fields of decision-making and conflict resolution
Specialties: project scheduling, optimization algorithms, ANP and group decision making
The Absolute Measurement in AHP/ANP: The Rating Mode and its Need for Thresholds
Glaudio Garuti Subtitle:
How to Know if Your Solution is Good Enough
The Power of Absolute Measurement in AHP/ANP
(The Power of AHP Rating Mode Assisted by Thresholds)
This workshop is oriented to understand and apply the absolute measurement mode of AHP (the rating mode), its need for thresholds and how to calculate it.
Requirements:
There are no special requirements. Although, it would be good to have some understanding about concepts as: scales, thresholds and compatibility (similarity).
Short Bio
Claudio Garuti, holds a Civil engineering title from the University of Chile and an M.Sc. from the University of Rome. He is currently the owner and manager of Fulcrum Engineering, CEO of the Medical Sapiens Society, and paper reviser in the IJAHP journal. He has more than 30 years of practice in decision-making with AHP/ANP in many different areas, such as medicine (medical decision support systems with topologic AI), risk assessment, disaster risk management, strategic environmental assessment, and public portfolio prioritization. He created the compatibility index G and wrote two books and several papers on AHP/ANP theory and applications. Also, he wrote a top-cited article in 2020–2021 in the Journal of multi-criteria decision Analysis for “A set theory justification of Garuti´s compatibility index”, received an Award of Excellence from the Creative Decision Foundation for the presentation of “How to assist to better and faster medical diagnose trough Medical Sapiens web platform”, and made several contributions to the AHP software “Total Decision web”.
His expertise spans decision-making theory, project evaluation, and optimization methods.
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