What is she best known for?
The fields of study she is best known for:
- Mathematical optimization
- Algorithm
- Programming language
Daniele Vigo spends much of her time researching Vehicle routing problem, Operations research, Mathematical optimization, Combinatorial optimization and Bin packing problem.
Her Vehicle routing problem study falls within the topics of Routing and Computer network.
Her work carried out in the field of Operations research brings together such families of science as Scheduling and Fleet management.
Her study looks at the relationship between Mathematical optimization and topics such as Set, which overlap with Relaxation and Branch and bound.
Her studies in Combinatorial optimization integrate themes in fields like Heuristic and Benchmark.
The study incorporates disciplines such as Cutting stock problem, Approximation algorithm and Metaheuristic in addition to Bin packing problem.
Her most cited work include:
- The vehicle routing problem (2805 citations)
- Models, relaxations and exact approaches for the capacitated vehicle routing problem (851 citations)
- A Survey of Optimization Models for Train Routing and Scheduling (632 citations)
What are the main themes of her work throughout her whole career to date?
Her primary scientific interests are in Vehicle routing problem, Mathematical optimization, Operations research, Routing and Algorithm.
Her Vehicle routing problem study combines topics in areas such as Combinatorial optimization and Benchmark.
Her work in Mathematical optimization tackles topics such as Set which are related to areas like Relaxation and Combinatorial optimization problem.
Her work carried out in the field of Operations research brings together such families of science as TRIPS architecture and Crew scheduling.
Her research in Algorithm intersects with topics in Scheduling and Heuristics.
Her Heuristic research is multidisciplinary, relying on both Genetic algorithm and Heuristic.
She most often published in these fields:
- Vehicle routing problem (49.16%)
- Mathematical optimization (41.90%)
- Operations research (27.37%)
What were the highlights of her more recent work (between 2018-2021)?
- Vehicle routing problem (49.16%)
- Routing (21.79%)
- Operations research (27.37%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Vehicle routing problem, Routing, Operations research, Mathematical optimization and Set.
Daniele Vigo merges Vehicle routing problem with Time windows in her research.
Her Routing research includes themes of Node and Quality of service.
In the field of Mathematical optimization, her study on Travelling salesman problem, Heuristic and Hybrid algorithm overlaps with subjects such as Arc.
The concepts of her Travelling salesman problem study are interwoven with issues in Iterated local search, Combinatorial optimization and Heuristics.
She usually deals with Computer network and limits it to topics linked to Relaxation and Heuristic.
Between 2018 and 2021, her most popular works were:
- A stochastic programming model for a tactical solid waste management problem (23 citations)
- Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights (14 citations)
- Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights (14 citations)
In her most recent research, the most cited papers focused on:
- Programming language
- Mathematical optimization
- Algorithm
The scientist’s investigation covers issues in Operations research, Vehicle routing problem, Set, Routing and Multiple time.
Her Operations research study frequently draws connections between adjacent fields such as Flow network.
Her Vehicle routing problem study typically links adjacent topics like Process.
Her studies link Data envelopment analysis with Set.
Her Routing research includes elements of Joint, Sequence, Incentive, Value and Schedule.
Her Multiple time study spans across into areas like Real-time computing, Time windows and Metaheuristic.
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