What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mathematical optimization
- Marketing
Stefan Voß mostly deals with Mathematical optimization, Operations research, Heuristics, Tabu search and Metaheuristic.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Transformation, Algorithm and Flow shop scheduling.
His research in Operations research intersects with topics in Berth allocation problem, Terminal, Production planning, Supply chain and Quay crane.
His Quay crane research integrates issues from Crane scheduling, Terminal operation, State, Containerization and Load planning.
His study looks at the intersection of Tabu search and topics like Optimization problem with Artificial intelligence and Decision problem.
His Metaheuristic research is multidisciplinary, incorporating elements of Scheduling, Local search, Software engineering and Extremal optimization.
His most cited work include:
- Container terminal operation and operations research — a classification and literature review (975 citations)
- Operations research at container terminals: a literature update (829 citations)
- Simple assembly line balancing—Heuristic approaches (160 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Mathematical optimization, Metaheuristic, Heuristics, Operations research and Tabu search.
His Mathematical optimization research is multidisciplinary, relying on both Algorithm and Benchmark.
Stefan Voß has included themes like Optimization problem, Local search, Ant colony optimization algorithms and GRASP in his Metaheuristic study.
His studies deal with areas such as Simple and Heuristic as well as Heuristics.
The various areas that Stefan Voß examines in his Operations research study include Supply chain and Berth allocation problem.
He combines subjects such as Simulated annealing and Travelling salesman problem with his study of Tabu search.
He most often published in these fields:
- Mathematical optimization (46.33%)
- Metaheuristic (22.04%)
- Heuristics (21.09%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (46.33%)
- Metaheuristic (22.04%)
- Set (8.95%)
In recent papers he was focusing on the following fields of study:
Stefan Voß spends much of his time researching Mathematical optimization, Metaheuristic, Set, Heuristics and Operations research.
His Mathematical optimization study integrates concerns from other disciplines, such as Quay crane and Benchmark.
His biological study spans a wide range of topics, including Ant colony optimization algorithms, Greedy algorithm and GRASP.
His work carried out in the field of Heuristics brings together such families of science as Variable, Quadratic assignment problem, Computational intelligence and State.
His studies in Operations research integrate themes in fields like Linear programming and Job shop scheduling.
As a member of one scientific family, Stefan Voß mostly works in the field of Berth allocation problem, focusing on Market share and, on occasion, Port.
Between 2017 and 2021, his most popular works were:
- An efficient ant colony optimization algorithm for the blocks relocation problem (27 citations)
- An efficient ant colony optimization algorithm for the blocks relocation problem (27 citations)
- A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Marketing
- Mathematical optimization
His primary scientific interests are in Mathematical optimization, Metaheuristic, Heuristics, Berth allocation problem and Greedy algorithm.
The Mathematical optimization study combines topics in areas such as Node, Supply chain management and Project scheduling problem.
His work deals with themes such as Ant colony optimization algorithms and GRASP, which intersect with Metaheuristic.
His Heuristics study frequently draws connections between adjacent fields such as Computational intelligence.
His Berth allocation problem study combines topics from a wide range of disciplines, such as Market share, Dynamic programming and Operations research.
While the research belongs to areas of Greedy algorithm, Stefan Voß spends his time largely on the problem of Heuristic, intersecting his research to questions surrounding Heuristic, State and Plan.
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