What is he best known for?
The fields of study he is best known for:
- Algorithm
- Mathematical optimization
- Programming language
David Pisinger focuses on Mathematical optimization, Continuous knapsack problem, Knapsack problem, Cutting stock problem and Change-making problem.
His Mathematical optimization study incorporates themes from Algorithm and Vehicle routing problem.
His Vehicle routing problem research includes elements of Search algorithm, Metaheuristic and Operations research.
His Continuous knapsack problem research incorporates themes from Quadratic programming, Lagrangian relaxation and Dynamic programming.
His Cutting stock problem research is multidisciplinary, relying on both Discrete mathematics and Subset sum problem.
His Change-making problem research is multidisciplinary, incorporating perspectives in Polynomial-time approximation scheme and Relaxation.
His most cited work include:
- An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows (1000 citations)
- A general heuristic for vehicle routing problems (887 citations)
- The Three-Dimensional Bin Packing Problem (422 citations)
What are the main themes of his work throughout his whole career to date?
David Pisinger mainly investigates Mathematical optimization, Knapsack problem, Operations research, Continuous knapsack problem and Liner shipping.
His research is interdisciplinary, bridging the disciplines of Algorithm and Mathematical optimization.
He interconnects Quadratic programming, Lagrangian relaxation, Approximation algorithm and Combinatorial optimization in the investigation of issues within Knapsack problem.
His Operations research research integrates issues from Port, Vehicle routing problem, Purchasing and Integer programming.
His work carried out in the field of Continuous knapsack problem brings together such families of science as Time complexity, Polynomial-time approximation scheme and Cutting stock problem.
His Heuristic study integrates concerns from other disciplines, such as Metaheuristic and Benchmark.
He most often published in these fields:
- Mathematical optimization (48.35%)
- Knapsack problem (21.43%)
- Operations research (20.33%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (48.35%)
- Operations research (20.33%)
- Column generation (8.79%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Mathematical optimization, Operations research, Column generation, Integer programming and Heuristic.
The study incorporates disciplines such as Quality and Selection in addition to Mathematical optimization.
David Pisinger interconnects Liner shipping, Container, Truck and Fuel efficiency in the investigation of issues within Operations research.
His research in Fuel efficiency intersects with topics in Time limit, Travelling salesman problem, Metaheuristic and Vehicle routing problem.
David Pisinger focuses mostly in the field of Integer programming, narrowing it down to topics relating to Robustness and, in certain cases, Stochastic modelling and Process.
His research on Heuristic also deals with topics like
- Scheduling which is related to area like Neighbourhood search,
- Graph, which have a strong connection to Shortest path problem, Heuristic, Decomposition, Benchmark and Set.
Between 2018 and 2021, his most popular works were:
- An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones (50 citations)
- Liner shipping network design (16 citations)
- Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview (6 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Programming language
- Mathematical optimization
David Pisinger mainly focuses on Mathematical optimization, Operations research, Routing, Port and Heuristics.
David Pisinger is involved in the study of Mathematical optimization that focuses on Heuristic in particular.
His biological study spans a wide range of topics, including Graph, Graph, Heuristic and Benchmark.
His Operations research research includes elements of Liner shipping, Integer programming and Fuel efficiency.
His Port study incorporates themes from Scheduling, Solver, Robustness and Neighbourhood search.
His studies in Heuristics integrate themes in fields like Level of service, Container, Multi-commodity flow problem and Revenue.
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