What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Gene
- Algorithm
Jacek Blazewicz spends much of his time researching Scheduling, Mathematical optimization, Flow shop scheduling, Job shop scheduling and Algorithm.
As part of his studies on Scheduling, Jacek Blazewicz often connects relevant subjects like Parallel computing.
His work on Simulated annealing as part of his general Mathematical optimization study is frequently connected to Resource constraints, thereby bridging the divide between different branches of science.
His work in Flow shop scheduling tackles topics such as Due date which are related to areas like List scheduling, Variable neighborhood search and Metaheuristic.
His work on Tabu search and Time complexity as part of general Algorithm study is frequently connected to Sequencing by hybridization, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Fair-share scheduling course of study focuses on Industrial engineering and Flexible manufacturing system, Real-time computing and Range.
His most cited work include:
- Scheduling subject to resource constraints: classification and complexity (1009 citations)
- Scheduling Computer and Manufacturing Processes (519 citations)
- The Job Shop Scheduling Problem: Conventional and new Solution Techniques (426 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Scheduling, Algorithm, Mathematical optimization, Parallel computing and Flow shop scheduling.
The concepts of his Scheduling study are interwoven with issues in Multiprocessing and Distributed computing.
His Tabu search study, which is part of a larger body of work in Algorithm, is frequently linked to Sequencing by hybridization, bridging the gap between disciplines.
His Mathematical optimization research integrates issues from Computational complexity theory and Time complexity.
His Parallel computing research is multidisciplinary, incorporating elements of Rate-monotonic scheduling, Gang scheduling and Fixed-priority pre-emptive scheduling.
Jacek Blazewicz works mostly in the field of DNA sequencing, limiting it down to concerns involving Bioinformatics and, occasionally, Set, Computational biology and RNA.
He most often published in these fields:
- Scheduling (26.75%)
- Algorithm (22.89%)
- Mathematical optimization (21.93%)
What were the highlights of his more recent work (between 2017-2021)?
- Scheduling (26.75%)
- Mathematical optimization (21.93%)
- RNA (16.14%)
In recent papers he was focusing on the following fields of study:
Jacek Blazewicz mainly investigates Scheduling, Mathematical optimization, RNA, Scheduling and Upper and lower bounds.
His Scheduling study incorporates themes from Computational complexity theory, Real-time computing and Parallel computing.
His Mathematical optimization research includes elements of Job shop scheduling and Flow shop scheduling.
In general Job shop scheduling study, his work on Machine scheduling often relates to the realm of Supply chain management, thereby connecting several areas of interest.
His RNA research incorporates elements of Normalized compression distance, Structure, Computational biology and Information retrieval.
His studies examine the connections between Scheduling and genetics, as well as such issues in Operations research, with regards to Scheduling theory and Time horizon.
Between 2017 and 2021, his most popular works were:
- RNApdbee 2.0: multifunctional tool for RNA structure annotation. (34 citations)
- RNApdbee 2.0: multifunctional tool for RNA structure annotation. (34 citations)
- Handbook on Scheduling : From Theory to Practice (9 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Gene
- Algorithm
His primary areas of study are Mathematical optimization, Job shop scheduling, Scheduling, RNA and Branch and bound.
His Mathematical optimization research is multidisciplinary, relying on both Computational complexity theory and Due date.
His Scheduling study frequently draws connections between adjacent fields such as Upper and lower bounds.
His RNA research incorporates themes from Base pair, Computational biology and Effector.
His studies deal with areas such as Structure, Web server, Nucleobase and Interface as well as Base pair.
His biological study spans a wide range of topics, including Genetic algorithm, Approximation algorithm, Maximization and Flow shop scheduling.
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