Jing J. Liang

Artificial Intelligence · 2005–2023

A researcher in the Science corpus: 12 papers; trusts 31 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 101 citations into it; #3,573 of 35,345 by trust here, #4,747 by citations
• Computational Theory and Mathematics — 69 citations into it; #1,214 of 12,182 by trust here, #669 by citations
• Electrical and Electronic Engineering — 26 citations into it
• Civil and Structural Engineering — 10 citations into it
• Genetics — 7 citations into it
• Control and Systems Engineering — 6 citations into it; #665 of 8,257 by trust here, #2,147 by citations
• Evaluation & Benchmarks — 5 citations into it
• Molecular Biology — 5 citations into it

Whom Jing J. Liang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kalyanmoy Deb
2. James Kennedy
3. Rui Mendes
4. R. Eberhart
5. Frans van den Bergh
6. Ponnuthurai Nagaratnam Suganthan
7. Ye Tian
8. Xiaodong Li
9. David Hilton Wolpert
10. Eckart Zitzler

Who trusts Jing J. Liang overall

1. Ran Cheng
2. Zhi-hui Zhan
3. Seyedali Mirjalili
4. Ponnuthurai Nagaratnam Suganthan
5. Jun Zhang
6. Yaochu Jin
7. Zahra Beheshti
8. Swagatam Das
9. Muhammad Rizwan Tanweer
10. Dongshu Wang

Papers from Jing J. Liang's perspective

Ordered by how strongly the researchers Jing J. Liang trusts endorse each paper. Same corpus, a different order for every researcher.

1. A fast and elitist multiobjective genetic algorithm: NSGA-II
2. No free lunch theorems for optimization
3. MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition (IEEE Transactions on Evolutionary Computation)
4. A new optimizer using particle swarm theory
5. Stochastic ranking for constrained evolutionary optimization (IEEE Transactions on Evolutionary Computation)
6. Constraint Handling in Multiobjective Evolutionary Optimization (IEEE Transactions on Evolutionary Computation)
7. An Efficient Constraint Handling Method for Genetic Algorithms
8. Scalable Test Problems for Evolutionary Multiobjective Optimization (Evolutionary Multiobjective Optimization)
9. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
10. SPEA2: Improving the strength pareto evolutionary algorithm

Their papers

• Comprehensive learning particle swarm optimizer for global optimization of multimodal functions (2006) — 3,597 citations
• Novel composition test functions for numerical global optimization (2005) — 464 citations
• Differential Evolution With Neighborhood Mutation for Multimodal Optimization (2012) — 414 citations
• A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems (2018) — 473 citations
• Dynamic multi-swarm particle swarm optimizer (2005) — 536 citations
• A self-adaptive global best harmony search algorithm for continuous optimization problems (2010) — 378 citations
• Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models (2018) — 357 citations
• A Survey on Evolutionary Constrained Multiobjective Optimization (2023) — 347 citations
• A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module (2019) — 412 citations
• Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization (2006) — 669 citations
• Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization (2005) — 3,161 citations
• Dynamic multi-swarm particle swarm optimizer with local search (2005) — 298 citations