George Mavrotas focuses on Mathematical optimization, Integer programming, Order, Combinatorial optimization and Energy planning. Mathematical optimization is frequently linked to Algorithm in his study. In his study, Linear programming is inextricably linked to Fuzzy logic, which falls within the broad field of Order.
His study looks at the relationship between Combinatorial optimization and fields such as Knapsack problem, as well as how they intersect with chemical problems. His Energy planning research includes elements of Data compression and Unit. His Pareto principle study combines topics from a wide range of disciplines, such as Process and Set packing.
His primary areas of study are Mathematical optimization, Operations research, Integer programming, Portfolio and Multiple-criteria decision analysis. His works in Pareto principle, Branch and bound, Combinatorial optimization, Knapsack problem and Linear programming are all subjects of inquiry into Mathematical optimization. In his works, George Mavrotas performs multidisciplinary study on Pareto principle and Programming paradigm.
His Operations research study integrates concerns from other disciplines, such as Multi-objective optimization, Order, Computational intelligence and Operations management. His studies in Integer programming integrate themes in fields like Electricity generation and Energy planning. He combines subjects such as Decision support system and Application portfolio management, Project portfolio management with his study of Portfolio.
The scientist’s investigation covers issues in Mathematical optimization, Portfolio, Integer programming, Combinatorial optimization and Pareto principle. His research integrates issues of Selection and Robustness in his study of Mathematical optimization. His work deals with themes such as Project portfolio management and Process, which intersect with Portfolio.
While the research belongs to areas of Project portfolio management, George Mavrotas spends his time largely on the problem of Operations research, intersecting his research to questions surrounding Operations management. His Integer programming research incorporates elements of Covering problems, Set cover problem and Travelling salesman problem. His work in Combinatorial optimization covers topics such as Knapsack problem which are related to areas like Deterministic algorithm.
George Mavrotas mostly deals with Multi-objective optimization, Mathematical optimization, Integer programming, Combinatorial optimization and Pareto principle. His work carried out in the field of Multi-objective optimization brings together such families of science as Distributed generation, Microgrid, Reliability engineering and Energy supply. The Mathematical optimization study combines topics in areas such as Modern portfolio theory, Robustness and Post-modern portfolio theory.
George Mavrotas interconnects Efficient frontier, Portfolio optimization and Portfolio in the investigation of issues within Robustness. He focuses mostly in the field of Integer programming, narrowing it down to topics relating to Knapsack problem and, in certain cases, Set packing. His study on Programming paradigm is intertwined with other disciplines of science such as Covering problems, Set cover problem, Travelling salesman problem and Algorithm.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems
Applied Mathematics and Computation (2009)
Determining objective weights in multiple criteria problems: the critic method
D. Diakoulaki;G. Mavrotas;L. Papayannakis.
Computers & Operations Research (1995)
An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems
George Mavrotas;Kostas Florios.
Applied Mathematics and Computation (2013)
Decomposition of industrial CO2 emissions:: The case of European Union
K. Liaskas;G. Mavrotas;M. Mandaraka;D. Diakoulaki.
Energy Economics (2000)
A branch and bound algorithm for mixed zero-one multiple objective linear programming
George Mavrotas;Danae Diakoulaki.
European Journal of Operational Research (1998)
A mathematical programming framework for energy planning in services’ sector buildings under uncertainty in load demand: The case of a hospital in Athens
George Mavrotas;Danae Diakoulaki;Kostas Florios;Paraskevas Georgiou.
Energy Policy (2008)
Development assistance and development finance: evidence and global policy agendas
Tony Addison;George Mavrotas;Mark McGillivray.
Journal of International Development (2005)
A bottom-up decomposition analysis of energy-related CO2 emissions in Greece
D. Diakoulaki;G. Mavrotas;D. Orkopoulos;L. Papayannakis.
PROJECT PRIORITIZATION UNDER POLICY RESTRICTIONS. A COMBINATION OF MCDA WITH 0–1 PROGRAMMING
George Mavrotas;Danae Diakoulaki;Y. Caloghirou.
European Journal of Operational Research (2006)
Selection among ranked projects under segmentation, policy and logical constraints
George Mavrotas;Danae Diakoulaki;Athanasios Kourentzis.
European Journal of Operational Research (2008)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: