What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Computer network
- Algorithm
His primary areas of investigation include Mathematical optimization, Operations research, Hub location problem, Linear programming and Heuristic.
His Algorithm research extends to Mathematical optimization, which is thematically connected.
His Operations research research incorporates themes from Scheduling and Scheduling.
His work deals with themes such as Computer network and Heuristic, which intersect with Hub location problem.
His Linear programming study combines topics in areas such as Integer programming and Branch and bound.
His Branch and bound research is multidisciplinary, incorporating elements of Heuristics and Data set.
His most cited work include:
- Staff scheduling and rostering: A review of applications, methods and models (926 citations)
- Efficient algorithms for the uncapacitated single allocation p-hub median problem (425 citations)
- An Annotated Bibliography of Personnel Scheduling and Rostering (367 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Integer programming, Operations research, Job shop scheduling and Network planning and design.
Heuristic, Heuristic, Simulated annealing, Linear programming and Column generation are the core of his Mathematical optimization study.
Algorithm covers Mohan Krishnamoorthy research in Heuristic.
His Linear programming study deals with Branch and bound intersecting with Data set and Benchmark.
His Integer programming study integrates concerns from other disciplines, such as Scheduling and Server.
His Facility location problem study, which is part of a larger body of work in Operations research, is frequently linked to Schedule, Product and Work, bridging the gap between disciplines.
He most often published in these fields:
- Mathematical optimization (58.59%)
- Integer programming (23.23%)
- Operations research (28.28%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (58.59%)
- Job shop scheduling (24.24%)
- Flow network (16.16%)
In recent papers he was focusing on the following fields of study:
Mohan Krishnamoorthy mainly investigates Mathematical optimization, Job shop scheduling, Flow network, Network planning and design and Heuristic.
His study on Integer programming is often connected to Remanufacturing as part of broader study in Mathematical optimization.
His Constructive heuristic and Machine scheduling study in the realm of Job shop scheduling connects with subjects such as Computational analysis and Fixed interval.
His work in Network planning and design covers topics such as Node which are related to areas like Survivability, Local search, Vehicle routing problem and Heuristic.
Mohan Krishnamoorthy combines subjects such as Deadline-monotonic scheduling, Assignment problem, Column generation, Heuristics and Dynamic priority scheduling with his study of Heuristic.
His Scheduling study combines topics in areas such as Overtaking and Ant colony.
Between 2017 and 2021, his most popular works were:
- Multi-period reverse logistics network design for used refrigerators (24 citations)
- Multi-period reverse logistics network design for used refrigerators (24 citations)
- Trends and directions in service triads research (14 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Mathematical optimization
- Algorithm
The scientist’s investigation covers issues in Mathematical optimization, Flow network, Network planning and design, Context and Node.
A majority of his Mathematical optimization research is a blend of other scientific areas, such as Profit maximization and Bill of materials.
His Flow network research is multidisciplinary, relying on both Column generation, Heuristic, Heuristics and Job shop scheduling.
His Network planning and design study frequently involves adjacent topics like Simulation.
His Context research incorporates a variety of disciplines, including Container, Hub location problem, Distribution and Distributed computing.
Mohan Krishnamoorthy merges Node with Set in his research.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
