His primary areas of study are Mathematical optimization, Genetic algorithm, Algorithm, Evolutionary algorithm and Evolutionary computation. The various areas that Dragan Savic examines in his Mathematical optimization study include Network performance, Optimal design and Sampling design. In general Genetic algorithm, his work in Meta-optimization is often linked to Pipe network analysis linking many areas of study.
His Algorithm study incorporates themes from Bayesian probability and Identification. His Evolutionary algorithm study combines topics from a wide range of disciplines, such as Water resources, Management science, Systems engineering and Water supply. His research in Evolutionary computation intersects with topics in Pareto principle, Genetic programming and Data mining.
His primary scientific interests are in Mathematical optimization, Distribution system, Operations research, Genetic algorithm and Distribution networks. His Mathematical optimization research incorporates themes from Optimal design and Benchmark. Dragan Savic combines Distribution system and Reliability engineering in his research.
Dragan Savic combines topics linked to Decision support system with his work on Operations research. Decision support system is often connected to Risk analysis in his work. His work deals with themes such as Calibration and Algorithm, which intersect with Genetic algorithm.
Distribution networks, Mathematical optimization, Evolutionary algorithm, Distribution system and Water resource management are his primary areas of study. His Distribution networks study frequently draws connections to other fields, such as Data mining. His work in the fields of Mathematical optimization, such as Multi-objective optimization and Genetic algorithm, intersects with other areas such as Leakage.
Dragan Savic interconnects Decision support system and Minification in the investigation of issues within Multi-objective optimization. His research integrates issues of Mutation operator, Mutation and Heuristics in his study of Evolutionary algorithm. He usually deals with Water resource management and limits it to topics linked to Critical infrastructure and Flood myth.
His main research concerns Distribution system, Mathematical optimization, Process, Multi-objective optimization and Flood myth. His studies in Mathematical optimization integrate themes in fields like Energy recovery and Simulation. Dragan Savic has researched Simulation in several fields, including Distribution networks, Solver, Evolutionary algorithm and Benchmark.
His study explores the link between Process and topics such as Simulated annealing that cross with problems in Network planning and design, Capital expenditure, Flexibility and Time horizon. His work carried out in the field of Flood myth brings together such families of science as Cellular automaton, Downscaling, Drainage and Environmental planning. The concepts of his Operations research study are interwoven with issues in Field, Drainage system and Water resources.
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Genetic Algorithms for Least-Cost Design of Water Distribution Networks
Dragan A. Savic;Godfrey A. Walters.
Advanced Water Distribution Modeling and Management
Thomas M. Walski;Donald V. Chase;Dragan A. Savic;Walter Grayman.
A review of methods for leakage management in pipe networks
R. Puust;Z. Kapelan;D. A. Savic;T. Koppel.
State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management
John Nicklow;Patrick Reed;Dragan Savic;Tibebe Dessalegne.
The battle of the water sensor networks (BWSN): A design challenge for engineers and algorithms
Avi Ostfeld;James G. Uber;Elad Salomons;Jonathan W. Berry.
Evolutionary algorithms and other metaheuristics in water resources
H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
Wastewater reuse in Europe
D. Bixio;C. Thoeye;J. De Koning;D. Joksimovic.
WATER NETWORK REHABILITATION WITH STRUCTURED MESSY GENETIC ALGORITHM
D. Halhal;G. A. Walters;D. Ouazar;D. A. Savic.
Evaluation of fuzzy linear regression models
Dragan A. Savic;Witold Pedrycz.
A symbolic data-driven technique based on evolutionary polynomial regression
Orazio Giustolisi;Dragan A. Savic.
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