People face multiple objectives and need to make decisions in a state of uncertainty on a regular basis. This volume shows how random-like multiple objective decision making can help readers deal with this problem.

What are the random-like phenomena that can be found everywhere in real-life world? When carrying out a random sampling survey on the traffic situation, we often obtain some descriptive results such as approximately expedite, a little crowded and so on, therefore, the average level should be regarded as the random fuzzy phenomenon, which is one of the random-like phenomena. Decision makers usually need to make the decision for these problems with random-like phenomena. Which model should be constructed for them? How should we handle these models to find the optimal strategy? How can we apply these models to solve real-life problems with random-like phenomena? In order to answer these questions, this book provides an up-to-date methodology system 5MRP for random-like multiple objective decision making, which includes problem system with random-like phenomena, model system with random-like coefficients, research system with random-like uncertain methods. Some practical applications are also provided to illustrate the effectiveness of the proposed methodology system. Researchers, practitioners and students in systems science, economics, mathematics, information, engineering and MS/OR will get a lot of useful references from this research monograph.

Numerous multi-objective programming models with random-like parameters help readers to solve realistic problems Hybrid intelligent algorithms help to solve multi-objective programming problems with random-like coefficients Practical applications show a realistic environment of the models A special chapter on the methodological system for RLMODM prepares readers for the future research Includes supplementary material: sn.pub/extras

Autorentext

This book is the result of a longstanding collaboration between two leading scholars. Professor Asaf Hajiyev, a full member of the Azerbaijan National Academy of Sciences, is renowned for his work in probability theory, mathematical statistics, and stochastic modeling. He has authored over 150 scientific papers and several books, and currently heads the Department of Statistical Modeling at the Institute of Control Systems. Professor Jiuping Xu, Distinguished Professor at Sichuan University and academician of several international academies, specializes in foundational modeling for computer science and management science. He has led over 80 national research projects and published more than 900 papers and 40 books. Together, their teams have developed innovative methodologies to evaluate the stability of AI interpretability using regression-based confidence regions. Their interdisciplinary partnership, active since 2010, combines theoretical rigor with practical insight to support robust and explainable decision-making in artificial intelligence.

Inhalt
Random Set Theory.- Random Multiple Objective Decision Making.- Bi-random Multiple Objective Decision Making.- Random Fuzzy Multiple Objective Decision Making.- Random Rough Multiple Objective Decision Making.- Methodological System for RLMODM.- Some Mathematical Aids.- Some Procedures.