What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algorithm
- Computer network
Mathematical optimization, Operations research, Queueing theory, Heuristics and Hypercube are his primary areas of study.
His Mathematical optimization research is multidisciplinary, incorporating elements of Algorithm and Container.
Reinaldo Morabito incorporates Operations research and Workload in his research.
His Queueing theory research is multidisciplinary, incorporating perspectives in Simulation and Service.
The study incorporates disciplines such as Scheduling, Graph, Heuristic and Pallet in addition to Heuristics.
His Hypercube research incorporates elements of Server and Backup.
His most cited work include:
- Metodologia de pesquisa em engenharia de produção e gestão de operações (147 citations)
- Solution approaches for the soft drink integrated production lot sizing and scheduling problem (125 citations)
- Three-dimensional container loading models with cargo stability and load bearing constraints (117 citations)
What are the main themes of his work throughout his whole career to date?
Reinaldo Morabito spends much of his time researching Mathematical optimization, Operations research, Integer programming, Queueing theory and Scheduling.
In general Mathematical optimization, his work in Heuristics, Heuristic and Solver is often linked to Sizing linking many areas of study.
His research integrates issues of Graph, Algorithm, Metaheuristic, Pallet and Container in his study of Heuristics.
His work deals with themes such as Linear programming and Scheduling, which intersect with Operations research.
His biological study deals with issues like Hypercube, which deal with fields such as Server and Backup.
Reinaldo Morabito integrates Scheduling and Production planning in his studies.
He most often published in these fields:
- Mathematical optimization (50.99%)
- Operations research (23.76%)
- Integer programming (18.32%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (50.99%)
- Integer programming (18.32%)
- Heuristic (7.92%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Integer programming, Heuristic, Scheduling and Heuristic.
The concepts of his Mathematical optimization study are interwoven with issues in Routing and Vehicle routing problem.
He interconnects Stochastic programming, Job shop scheduling and Operations research in the investigation of issues within Integer programming.
His Operations research research integrates issues from Travelling salesman problem, Service system and Tabu search.
Reinaldo Morabito works mostly in the field of Scheduling, limiting it down to topics relating to Scheduling and, in certain cases, Ship routing and Computation.
His Heuristic research is multidisciplinary, relying on both Branch and cut, Branch and price and Directed acyclic graph.
Between 2017 and 2021, his most popular works were:
- Iterated local search and simulated annealing algorithms for the inventory routing problem (20 citations)
- Benders decomposition applied to a robust multiple allocation incomplete hub location problem (20 citations)
- An integrated approach for production lot sizing and raw material purchasing (13 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Mathematical optimization
- Mechanical engineering
His scientific interests lie mostly in Mathematical optimization, Operations research, Integer programming, Robust optimization and Heuristic.
His work in Mathematical optimization addresses issues such as Benchmark, which are connected to fields such as Solver.
His Operations research study combines topics from a wide range of disciplines, such as Scheduling and Purchasing.
His work carried out in the field of Integer programming brings together such families of science as Travelling salesman problem, Tabu search and Batch production.
His study looks at the intersection of Robust optimization and topics like Benders' decomposition with Hub location problem and Algorithm.
His study looks at the relationship between Heuristic and topics such as Heuristic, which overlap with Local search.
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