What is she best known for?
The fields of study she is best known for:
- Algorithm
- Mathematical optimization
- Linear programming
Her main research concerns Mathematical optimization, Combinatorics, Set packing, Heuristic and Metaheuristic.
Michele Monaci has included themes like Algorithm, Robustness and Operations research in her Mathematical optimization study.
Michele Monaci interconnects Discrete mathematics and Knapsack problem in the investigation of issues within Combinatorics.
Her studies in Set packing integrate themes in fields like Bin packing problem and Heuristic.
Her Heuristic research includes elements of Routing and Vehicle routing problem.
The study incorporates disciplines such as Branch and bound, Strip packing problem, Approximation algorithm and Packing problems in addition to Square packing in a square.
Her most cited work include:
- Two-dimensional packing problems: A survey (659 citations)
- An Exact Approach to the Strip-Packing Problem (221 citations)
- Passenger Railway Optimization (199 citations)
What are the main themes of her work throughout her whole career to date?
Michele Monaci mainly focuses on Mathematical optimization, Algorithm, Integer programming, Knapsack problem and Bin packing problem.
Her Mathematical optimization research focuses on Heuristic, Heuristics, Heuristic, Solver and Metaheuristic.
Her Algorithm research incorporates elements of Column generation and Scheduling.
Her Integer programming study combines topics in areas such as Linear programming and Stochastic programming.
Her study in Knapsack problem is interdisciplinary in nature, drawing from both Dynamic programming and Combinatorics.
The concepts of her Bin packing problem study are interwoven with issues in Combinatorial optimization, Set packing and Packing problems.
She most often published in these fields:
- Mathematical optimization (46.67%)
- Algorithm (26.67%)
- Integer programming (21.11%)
What were the highlights of her more recent work (between 2018-2021)?
- Heuristic (16.67%)
- Knapsack problem (16.67%)
- Mathematical optimization (46.67%)
In recent papers she was focusing on the following fields of study:
Her primary areas of study are Heuristic, Knapsack problem, Mathematical optimization, Algorithm and Optimization problem.
She has researched Heuristic in several fields, including Genetic algorithm, Industrial engineering and Heuristic.
Her work carried out in the field of Knapsack problem brings together such families of science as Approximation algorithm and Metaheuristic.
Her Approximation algorithm study incorporates themes from Scheduling, Dynamic programming, Mathematical model and Continuous knapsack problem.
Her Mathematical optimization study frequently draws connections to adjacent fields such as Data set.
Her Algorithm research integrates issues from Maximum flow problem and Benchmark.
Between 2018 and 2021, her most popular works were:
- Interdiction Games and Monotonicity, with Application to Knapsack Problems (23 citations)
- Algorithmic approaches to the multiple knapsack assignment problem (8 citations)
- A Branch-and-Cut Algorithm for Mixed-Integer Bilinear Programming (5 citations)
In her most recent research, the most cited papers focused on:
- Algorithm
- Mathematical optimization
- Computer network
Her primary areas of investigation include Knapsack problem, Mathematical optimization, Branch and cut, Metaheuristic and Computational complexity theory.
Her research in Knapsack problem intersects with topics in Bilevel optimization and Operations research.
As part of her studies on Mathematical optimization, Michele Monaci often connects relevant areas like Mathematical model.
The Branch and cut study combines topics in areas such as Quadratic programming, Solver and Combinatorial optimization.
She combines subjects such as Assignment problem and Constructive heuristic with her study of Metaheuristic.
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