H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Mathematics H-index 84 Citations 31,285 606 World Ranking 51 National Ranking 31
Computer Science H-index 86 Citations 31,657 633 World Ranking 314 National Ranking 197

Research.com Recognitions

Awards & Achievements

2016 - Fellow of the Indian National Academy of Engineering (INAE)

2013 - EURO Gold Medal

2006 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)

2004 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Mathematical optimization
  • Statistics

His primary areas of investigation include Mathematical optimization, Algorithm, Global optimization, Quadratic programming and Combinatorial optimization. His Mathematical optimization study deals with Quadratic equation intersecting with Branch and bound. His studies deal with areas such as Assignment problem, Job shop scheduling and Electroencephalography as well as Algorithm.

In his study, which falls under the umbrella issue of Global optimization, Field is strongly linked to Nonlinear programming. Panos M. Pardalos has researched Quadratic programming in several fields, including Discrete mathematics, Quadratic unconstrained binary optimization, Second-order cone programming and Combinatorics. Panos M. Pardalos combines subjects such as Theoretical computer science, Approximation algorithm and Heuristics with his study of Combinatorial optimization.

His most cited work include:

  • Handbook of global optimization (1240 citations)
  • Introduction to global optimization (980 citations)
  • Handbook of Combinatorial Optimization (830 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Mathematical optimization, Algorithm, Artificial intelligence, Global optimization and Optimization problem. As part of his studies on Mathematical optimization, Panos M. Pardalos often connects relevant areas like Job shop scheduling. His Job shop scheduling study is related to the wider topic of Scheduling.

His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition.

He most often published in these fields:

  • Mathematical optimization (34.90%)
  • Algorithm (14.12%)
  • Artificial intelligence (10.28%)

What were the highlights of his more recent work (between 2016-2021)?

  • Mathematical optimization (34.90%)
  • Algorithm (14.12%)
  • Job shop scheduling (4.27%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Mathematical optimization, Algorithm, Job shop scheduling, Optimization problem and Artificial intelligence. His Mathematical optimization research is multidisciplinary, relying on both Vehicle routing problem and Theory of computation. Many of his studies on Algorithm involve topics that are commonly interrelated, such as Function.

His research on Job shop scheduling often connects related topics like Scheduling. His studies link Machine learning with Artificial intelligence. Many of his studies involve connections with topics such as Learning effect and Scheduling.

Between 2016 and 2021, his most popular works were:

  • Quantification of network structural dissimilarities (101 citations)
  • A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers (62 citations)
  • A hybrid BA-VNS algorithm for coordinated serial-batching scheduling with deteriorating jobs, financial budget, and resource constraint in multiple manufacturers (62 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Mathematical optimization

His primary scientific interests are in Mathematical optimization, Job shop scheduling, Algorithm, Scheduling and Scheduling. His research brings together the fields of Supply chain and Mathematical optimization. Within one scientific family, Panos M. Pardalos focuses on topics pertaining to Resource under Job shop scheduling, and may sometimes address concerns connected to Finance and Bat algorithm.

Panos M. Pardalos combines subjects such as Simplex, Support vector machine and Extension with his study of Algorithm. His Heuristic research integrates issues from Local search and Heuristics. In his research on the topic of Local search, Optimization problem is strongly related with Benchmark.

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.

Top Publications

Introduction to global optimization

Reiner Horst;Panos M Pardalos;Nguyen V Van Thoai.
Published in <b>1995</b> in Dordrecht by Kluwer (1995)

1521 Citations

Handbook of global optimization

Reiner Horst;P. M. Pardalos;H. Edwin Romeijn.
(1995)

1510 Citations

Handbook of Combinatorial Optimization

Ding-Zhu Du;Panos M. Pardalos.
(1998)

1229 Citations

Nonconvex Optimization and Its Applications

Panos Pardalos;Shashi Kant Mishra;Shou-Yang Wang;Kin Keung Lai.
(2008)

1174 Citations

The Maximum Clique Problem.

Immanuel M. Bomze;Marco Budinich;Panos M. Pardalos;Marcello Pelillo.
Handbook of Combinatorial Optimization (1999)

1077 Citations

Encyclopedia of Optimization

Christodoulos C. A. Floudas;P. M. Pardalos.
(2006)

824 Citations

Handbook of applied optimization

P. M. Pardalos;Mauricio G. C. Resende.
(2002)

795 Citations

A Collection of Test Problems for Constrained Global Optimization Algorithms

Christodoulos A. Floudas;Panos M. Pardalos.
(1990)

773 Citations

An exact algorithm for the maximum clique problem

Randy Carraghan;Panos M. Pardalos.
Operations Research Letters (1990)

703 Citations

Constrained Global Optimization: Algorithms and Applications

Panos M. Pardalos;J. Ben Rosen.
(1987)

645 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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