What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algorithm
- Scheduling
His primary scientific interests are in Mathematical optimization, Scheduling, Time complexity, Single-machine scheduling and Dynamic programming.
His Mathematical optimization research incorporates elements of Completion time, Job scheduler, Computational complexity theory and Tardiness.
The concepts of his Scheduling study are interwoven with issues in Scheduling, Resource allocation and Operations research.
His biological study spans a wide range of topics, including Sequence-dependent setup, Genetic algorithm, Open shop and Job shop.
Mikhail Y. Kovalyov works mostly in the field of Single-machine scheduling, limiting it down to topics relating to Group technology and, in certain cases, Resource.
His Dynamic programming study incorporates themes from Dynamic priority scheduling and Inventory control.
His most cited work include:
- A survey of scheduling problems with setup times or costs (1058 citations)
- Scheduling with batching: A review (757 citations)
- Scheduling a batching machine (335 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Mathematical optimization, Scheduling, Time complexity, Computational complexity theory and Dynamic programming.
His Mathematical optimization research integrates issues from Job scheduler and Single-machine scheduling, Job shop scheduling.
His work focuses on many connections between Job scheduler and other disciplines, such as Scheduling, that overlap with his field of interest in Industrial engineering, Distributed computing and Dynamic priority scheduling.
His Scheduling research focuses on Algorithm and how it connects with Computer experiment.
His Time complexity study integrates concerns from other disciplines, such as Multiprocessor scheduling, Approximation algorithm and Heuristic.
His Computational complexity theory research is multidisciplinary, incorporating perspectives in Machine scheduling and Heuristics.
He most often published in these fields:
- Mathematical optimization (59.51%)
- Scheduling (45.85%)
- Time complexity (26.83%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (59.51%)
- Scheduling (45.85%)
- Time complexity (26.83%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Scheduling, Time complexity, Computational complexity theory and Combinatorics.
Many of his research projects under Mathematical optimization are closely connected to Assembly line and Line with Assembly line and Line, tying the diverse disciplines of science together.
His research on Dynamic programming frequently connects to adjacent areas such as Flow shop scheduling.
Mikhail Y. Kovalyov has researched Scheduling in several fields, including Operations research and Parallel computing.
His Time complexity research incorporates themes from Completion time and Exact algorithm.
His studies deal with areas such as Resource and Combinatorial optimization as well as Computational complexity theory.
Between 2015 and 2021, his most popular works were:
- Optimal workforce assignment to operations of a paced assembly line (17 citations)
- Minimizing the number of workers in a paced mixed-model assembly line (10 citations)
- Integrated production scheduling and batch delivery with fixed departure times and inventory holding costs (10 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Algorithm
- Scheduling
Mikhail Y. Kovalyov focuses on Scheduling, Mathematical optimization, Scheduling, Computational complexity theory and Parallel computing.
The study incorporates disciplines such as Assignment problem and General position in addition to Scheduling.
He works on Mathematical optimization which deals in particular with Dynamic programming.
The study of Dynamic programming is intertwined with the study of Flow shop scheduling in a number of ways.
His Scheduling research includes themes of Integrated production, Holding cost and Industrial engineering.
His Computational complexity theory study incorporates themes from Schedule and Combinatorial optimization.
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