D-Index & Metrics Best Publications
Computer Science
Australia
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Mathematics D-index 54 Citations 9,082 324 World Ranking 628 National Ranking 15
Computer Science D-index 56 Citations 9,688 351 World Ranking 2738 National Ranking 61

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Australia Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Mathematical optimization
  • Algorithm

Ruhul A. Sarker mostly deals with Mathematical optimization, Evolutionary algorithm, Genetic algorithm, Optimization problem and Operations research. His Mathematical optimization study frequently draws parallels with other fields, such as Benchmark. His Evolutionary algorithm study integrates concerns from other disciplines, such as Population-based incremental learning, Cultural algorithm and Pareto principle.

His Genetic algorithm research includes themes of Algorithm and Job shop scheduling. Ruhul A. Sarker has researched Optimization problem in several fields, including Multi-objective optimization and Algorithm design. His Operations research research incorporates elements of Quality, Linear programming, Time horizon and Heuristic.

His most cited work include:

  • PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems (433 citations)
  • Evolutionary Optimization (219 citations)
  • A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization (211 citations)

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

His primary areas of study are Mathematical optimization, Evolutionary algorithm, Optimization problem, Genetic algorithm and Evolutionary computation. His biological study spans a wide range of topics, including Job shop scheduling and Benchmark. His Evolutionary algorithm research is multidisciplinary, incorporating elements of Heuristic, Process and Cultural algorithm.

Ruhul A. Sarker interconnects Multi-objective optimization, Metaheuristic and Crossover in the investigation of issues within Optimization problem. His study focuses on the intersection of Genetic algorithm and fields such as Heuristic with connections in the field of Operations research. Ruhul A. Sarker combines subjects such as Range, Selection and Evolution strategy with his study of Differential evolution.

He most often published in these fields:

  • Mathematical optimization (57.56%)
  • Evolutionary algorithm (33.14%)
  • Optimization problem (23.55%)

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

  • Mathematical optimization (57.56%)
  • Optimization problem (23.55%)
  • Evolutionary algorithm (33.14%)

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

Ruhul A. Sarker mostly deals with Mathematical optimization, Optimization problem, Evolutionary algorithm, Differential evolution and Genetic algorithm. His study looks at the relationship between Mathematical optimization and fields such as Process, as well as how they intersect with chemical problems. His research in Optimization problem focuses on subjects like Microgrid, which are connected to Operating cost.

The study incorporates disciplines such as Evolutionary computation, Optimization algorithm, Algorithm design and Benchmark in addition to Evolutionary algorithm. The concepts of his Differential evolution study are interwoven with issues in Scheduling, Selection and Genetic operator. As part of one scientific family, he deals mainly with the area of Genetic algorithm, narrowing it down to issues related to the Segmentation, and often Network topology.

Between 2016 and 2021, his most popular works were:

  • Resource constrained project scheduling with uncertain activity durations (50 citations)
  • A quantitative model for disruption mitigation in a supply chain (48 citations)
  • On solving periodic re-optimization dynamic vehicle routing problems (37 citations)

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

  • Artificial intelligence
  • Mathematical optimization
  • Algorithm

His scientific interests lie mostly in Mathematical optimization, Optimization problem, Evolutionary algorithm, Differential evolution and Evolutionary computation. Ruhul A. Sarker integrates Mathematical optimization and Profit in his studies. His research combines Genetic algorithm and Optimization problem.

He has researched Evolutionary algorithm in several fields, including Algorithm design and Computational intelligence. Ruhul A. Sarker interconnects Bidding, Selection and Genetic operator in the investigation of issues within Differential evolution. His Evolutionary computation research is multidisciplinary, incorporating perspectives in Pareto principle, Ecological selection and 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.

Best Publications

PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems

H.A. Abbass;R. Sarker;C. Newton.
congress on evolutionary computation (2001)

734 Citations

A Decomposition-Based Evolutionary Algorithm for Many Objective Optimization

M. Asafuddoula;Tapabrata Ray;Ruhul Sarker.
IEEE Transactions on Evolutionary Computation (2015)

326 Citations

Data Mining: A Heuristic Approach

Hussein Abbass;Charles Newton;Ruhul Sarker.
(2002)

241 Citations

Differential Evolution With Dynamic Parameters Selection for Optimization Problems

Ruhul A. Sarker;Saber M. Elsayed;Tapabrata Ray.
IEEE Transactions on Evolutionary Computation (2014)

240 Citations

THE PARETO DIFFERENTIAL EVOLUTION ALGORITHM

Hussein A. Abbass;Ruhul A. Sarker.
International Journal on Artificial Intelligence Tools (2002)

240 Citations

Optimization of maintenance and spare provisioning policy using simulation

Ruhul Sarker;Amanul Haque.
Applied Mathematical Modelling (2000)

220 Citations

Evolutionary Optimization

Ruhul Sarker;Xin Yao.
(2002)

219 Citations

Multi-operator based evolutionary algorithms for solving constrained optimization problems

Saber M. Elsayed;Ruhul A. Sarker;Daryl L. Essam.
Computers & Operations Research (2011)

201 Citations

A new genetic algorithm for solving optimization problems

Saber M. Elsayed;Ruhul A. Sarker;Daryl L. Essam.
Engineering Applications of Artificial Intelligence (2014)

189 Citations

An improved evolutionary algorithm for solving multi-objective crop planning models

Ruhul Sarker;Tapabrata Ray.
Computers and Electronics in Agriculture (2009)

169 Citations

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