What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Artificial intelligence
- Algorithm
His main research concerns Scheduling, Mathematical optimization, Operations research, Scheduling and Schedule.
His studies in Scheduling integrate themes in fields like Ant colony optimization algorithms, Metaheuristic and Branch and bound.
His studies examine the connections between Branch and bound and genetics, as well as such issues in Job shop, with regards to Rate-monotonic scheduling.
His Mathematical optimization research incorporates themes from Disjunctive graph, Multiprocessor scheduling and Flow shop scheduling.
His Operations research study which covers Transport engineering that intersects with Real-time Control System.
His work deals with themes such as Total cost, Upper and lower bounds and Time complexity, which intersect with Scheduling.
His most cited work include:
- A branch and bound algorithm for scheduling trains in a railway network (398 citations)
- Scheduling Problems with Two Competing Agents (337 citations)
- Job-shop scheduling with blocking and no-wait constraints (326 citations)
What are the main themes of his work throughout his whole career to date?
Dario Pacciarelli mainly investigates Mathematical optimization, Scheduling, Operations research, Job shop scheduling and Scheduling.
As a member of one scientific family, he mostly works in the field of Mathematical optimization, focusing on Tardiness and, on occasion, Sequence.
In his study, which falls under the umbrella issue of Scheduling, Quality of service and Upper and lower bounds is strongly linked to Computation.
His studies deal with areas such as Ant colony optimization algorithms, Transport engineering, Schedule, Decision support system and Bottleneck as well as Operations research.
His Flow shop scheduling, Job shop, Disjunctive graph and Nurse scheduling problem investigations are all subjects of Job shop scheduling research.
His Flow shop scheduling study combines topics in areas such as Rate-monotonic scheduling and Heuristics.
He most often published in these fields:
- Mathematical optimization (43.51%)
- Scheduling (28.24%)
- Operations research (26.72%)
What were the highlights of his more recent work (between 2014-2020)?
- Mathematical optimization (43.51%)
- Job shop scheduling (24.43%)
- Scheduling (28.24%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Mathematical optimization, Job shop scheduling, Scheduling, Operations research and Computation.
His Mathematical optimization study frequently links to other fields, such as Upper and lower bounds.
His work on Flow shop scheduling as part of general Job shop scheduling research is frequently linked to Terminal control area, bridging the gap between disciplines.
His Scheduling research is multidisciplinary, incorporating perspectives in Linear programming and Fuel efficiency.
His Operations research research integrates issues from Distributed computing and Ant colony optimization algorithms.
His work carried out in the field of Computation brings together such families of science as Schedule, Quality of service, Scheduling and Real-time Control System.
Between 2014 and 2020, his most popular works were:
- Integrating train scheduling and delay management in real-time railway traffic control (101 citations)
- Ant colony optimization for the real-time train routing selection problem (79 citations)
- A variable neighbourhood search for fast train scheduling and routing during disturbed railway traffic situations (67 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mathematical optimization
- Algorithm
The scientist’s investigation covers issues in Job shop scheduling, Mathematical optimization, Operations research, Metaheuristic and Terminal control area.
Dario Pacciarelli studies Flow shop scheduling which is a part of Job shop scheduling.
His research integrates issues of Dynamic priority scheduling and Fair-share scheduling in his study of Mathematical optimization.
His study ties his expertise on Scheduling together with the subject of Operations research.
His Metaheuristic study incorporates themes from Ant colony optimization algorithms and Ant colony.
His Tabu search research includes themes of Takeoff, Metaheuristic algorithms, Branch and bound, Heuristic and Linear programming.
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