What is he best known for?
The fields of study he is best known for:
- Algorithm
- Mathematical optimization
- Scheduling
His primary scientific interests are in Scheduling, Mathematical optimization, Job shop scheduling, Heuristics and Algorithm.
He is involved in the study of Scheduling that focuses on Fixed-priority pre-emptive scheduling in particular.
His studies in Mathematical optimization integrate themes in fields like Completion time, Upper and lower bounds, Theory of computation and Tardiness.
His Multiprocessor scheduling study in the realm of Job shop scheduling connects with subjects such as Preemption.
Joseph Y.-T. Leung combines subjects such as Discrete mathematics, Interval scheduling, Parallel computing, Gang scheduling and Open-shop scheduling with his study of Multiprocessor scheduling.
His Heuristics research is multidisciplinary, incorporating perspectives in Berth allocation problem, Product type, Time horizon and Computational complexity theory.
His most cited work include:
- On the complexity of fixed-priority scheduling of periodic, real-time tasks (1008 citations)
- Handbook of Scheduling: Algorithms, Models, and Performance Analysis (845 citations)
- Minimizing total tardiness on one machine is NP-hard (602 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Mathematical optimization, Scheduling, Job shop scheduling, Time complexity and Algorithm.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Upper and lower bounds and Set.
His work on Multiprocessor scheduling as part of general Scheduling study is frequently linked to Preemption, therefore connecting diverse disciplines of science.
His Job shop scheduling study incorporates themes from Competitive analysis and Heuristic.
His Time complexity research includes themes of Due date, Imprecise computation and Tardiness.
His study in Fair-share scheduling is interdisciplinary in nature, drawing from both Flow shop scheduling and Parallel computing.
He most often published in these fields:
- Mathematical optimization (60.18%)
- Scheduling (57.08%)
- Job shop scheduling (44.25%)
What were the highlights of his more recent work (between 2014-2019)?
- Mathematical optimization (60.18%)
- Scheduling (57.08%)
- Job shop scheduling (44.25%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Scheduling, Job shop scheduling, Scheduling and Heuristics.
His Scheduling research incorporates elements of Distributed computing, Minification and Computational complexity theory, Algorithm, Approximation algorithm.
The Approximation algorithm study combines topics in areas such as Job scheduler and Batch machine.
His research integrates issues of Upper and lower bounds and Industrial engineering in his study of Job shop scheduling.
He performs integrative study on Scheduling and Total cost.
His Heuristics study frequently links to related topics such as Real-time computing.
Between 2014 and 2019, his most popular works were:
- Integrated scheduling of production and distribution to minimize total cost using an improved ant colony optimization method (43 citations)
- Parallel machine scheduling problems in green manufacturing industry (41 citations)
- Parallel machine scheduling problems in green manufacturing industry (41 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Mathematical optimization
- Scheduling
Joseph Y.-T. Leung mainly investigates Job shop scheduling, Scheduling, Mathematical optimization, Scheduling and Heuristics.
His Job shop scheduling research incorporates themes from Representation and Heuristic.
His work carried out in the field of Heuristic brings together such families of science as Ant colony optimization algorithms and Minification.
His research in Scheduling focuses on subjects like Computational complexity theory, which are connected to Theoretical computer science, Test data and Meta heuristic.
His studies deal with areas such as Upper and lower bounds and Decision model as well as Mathematical optimization.
His Upper and lower bounds research is multidisciplinary, incorporating elements of Distributed computing, Job scheduler, Iterated greedy algorithm and Greedy algorithm.
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