What is she best known for?
The fields of study she is best known for:
- Mathematical optimization
- Statistics
- Algorithm
Her primary areas of investigation include Mathematical optimization, Integer programming, Algorithm, Bin packing problem and Combinatorial optimization.
Her Mathematical optimization study combines topics in areas such as Nonlinear programming and Integer.
Her work in the fields of Integer programming, such as Cutting-plane method, intersects with other areas such as Numerical analysis.
Her Algorithm research is multidisciplinary, incorporating perspectives in Software, Relaxation, Optimal design and Benchmark.
Andrea Lodi interconnects Set, Theory of computation, Tabu search and Packing problems in the investigation of issues within Bin packing problem.
She has included themes like Optimization problem and Solver in her Combinatorial optimization study.
Her most cited work include:
- An algorithmic framework for convex mixed integer nonlinear programs (678 citations)
- Two-dimensional packing problems: A survey (659 citations)
- Heuristic and Metaheuristic Approaches for a Class of Two-Dimensional Bin Packing Problems (285 citations)
What are the main themes of her work throughout her whole career to date?
Andrea Lodi spends much of her time researching Mathematical optimization, Integer programming, Algorithm, Combinatorics and Combinatorial optimization.
The various areas that she examines in her Mathematical optimization study include Constraint programming and Integer.
Her research on Integer programming often connects related topics like Heuristic.
Her Combinatorics research is multidisciplinary, relying on both Discrete mathematics and Knapsack problem.
Her Combinatorial optimization study combines topics from a wide range of disciplines, such as Optimization problem and Theoretical computer science.
The concepts of her Relaxation study are interwoven with issues in Travelling salesman problem and Constraint.
She most often published in these fields:
- Mathematical optimization (43.69%)
- Integer programming (20.71%)
- Algorithm (12.94%)
What were the highlights of her more recent work (between 2018-2021)?
- Mathematical optimization (43.69%)
- Solver (10.03%)
- Integer programming (20.71%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Mathematical optimization, Solver, Integer programming, Combinatorial optimization and Artificial intelligence.
Andrea Lodi combines subjects such as Computational complexity theory, Set and Benchmark with her study of Mathematical optimization.
Her Solver research is multidisciplinary, incorporating elements of Linear programming, Component and Parallel computing.
Integer programming is the subject of her research, which falls under Algorithm.
Her Combinatorial optimization research incorporates themes from Graph, Optimization problem, Theoretical computer science and Code.
Her Artificial intelligence research incorporates elements of Machine learning and Key.
Between 2018 and 2021, her most popular works were:
- Machine learning for combinatorial optimization: A methodological tour d’horizon (145 citations)
- Exact Combinatorial Optimization with Graph Convolutional Neural Networks (31 citations)
- Exact Combinatorial Optimization with Graph Convolutional Neural Networks (26 citations)
In her most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Programming language
Andrea Lodi mainly focuses on Mathematical optimization, Solver, Combinatorial optimization, Integer programming and Key.
Her Mathematical optimization research focuses on Facility location problem in particular.
Her study in Solver is interdisciplinary in nature, drawing from both Graph, Bipartite graph, Graph, Convolutional neural network and Feature selection.
Her Combinatorial optimization research integrates issues from Discrete optimization problem, Theoretical computer science and Artificial intelligence.
As part of the same scientific family, Andrea Lodi usually focuses on Integer programming, concentrating on Perceptron and intersecting with Inference and Ask price.
Andrea Lodi has researched Benchmark in several fields, including Tree, Linear programming and Branch and bound.
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