What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Computer network
- Artificial intelligence
Dominique Feillet mainly focuses on Mathematical optimization, Vehicle routing problem, Column generation, Operations research and Routing.
His 2-opt, Travelling salesman problem and Memetic algorithm study in the realm of Mathematical optimization interacts with subjects such as Context and Shortest path problem.
His work on Constrained Shortest Path First, Longest path problem and K shortest path routing as part of his general Shortest path problem study is frequently connected to Private Network-to-Network Interface and Algorithm, thereby bridging the divide between different branches of science.
His Vehicle routing problem research incorporates elements of City logistics, Transport engineering and Principal.
Dominique Feillet focuses mostly in the field of Column generation, narrowing it down to topics relating to Orienteering and, in certain cases, Branch and price, Tabu search, Heuristic and Purchasing.
The concepts of his Operations research study are interwoven with issues in Service quality, Truck and Project management.
His most cited work include:
- An exact algorithm for the elementary shortest path problem with resource constraints: Application to some vehicle routing problems (477 citations)
- Traveling Salesman Problems with Profits (462 citations)
- An exact algorithm for team orienteering problems (152 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Vehicle routing problem, Operations research, Routing and Context.
His Travelling salesman problem, Branch and price, Column generation and Dynamic programming study, which is part of a larger body of work in Mathematical optimization, is frequently linked to Set, bridging the gap between disciplines.
His study in Travelling salesman problem is interdisciplinary in nature, drawing from both Scheduling and Ant colony optimization algorithms.
His Vehicle routing problem study frequently links to adjacent areas such as TRIPS architecture.
His Operations research study incorporates themes from Competition, Orienteering and Heuristic.
His work in Routing tackles topics such as Heuristic which are related to areas like Quality.
He most often published in these fields:
- Mathematical optimization (41.94%)
- Vehicle routing problem (30.65%)
- Operations research (29.84%)
What were the highlights of his more recent work (between 2016-2021)?
- Mathematical optimization (41.94%)
- Vehicle routing problem (30.65%)
- Heuristic (12.10%)
In recent papers he was focusing on the following fields of study:
Dominique Feillet spends much of his time researching Mathematical optimization, Vehicle routing problem, Heuristic, Routing and Branch and price.
His work on Travelling salesman problem and Exact algorithm as part of general Mathematical optimization research is frequently linked to Sequence, thereby connecting diverse disciplines of science.
The Vehicle routing problem study combines topics in areas such as Travel time and City logistics.
Dominique Feillet combines subjects such as Completion time, Dynamic programming, Heuristic and Operations research with his study of Heuristic.
In the subject of general Routing, his work in Inventory routing problem is often linked to Integrated approach, thereby combining diverse domains of study.
His Branch and price research incorporates themes from Column generation and Reduced cost.
Between 2016 and 2021, his most popular works were:
- Vehicle routing problems for city logistics (113 citations)
- An iterative two‐step heuristic for the parallel drone scheduling traveling salesman problem (25 citations)
- Empirical analysis for the VRPTW with a multigraph representation for the road network (24 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Computer network
- Artificial intelligence
His scientific interests lie mostly in Vehicle routing problem, Mathematical optimization, Multigraph, Branch and price and Time windows.
His biological study spans a wide range of topics, including City logistics, Transport engineering and Principal.
His work blends Mathematical optimization and Distribution studies together.
His work deals with themes such as Representation and Key, which intersect with Branch and price.
His Dynamic programming research is multidisciplinary, incorporating perspectives in Travelling salesman problem and Decoding methods.
As part of his studies on Heuristic, he often connects relevant areas like Operations research.
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