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Hemant K. Singh
Hemant Kumar Singh
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2020 – today
- 2024
- [j32]Rounak Saha Niloy
, Hemant Kumar Singh
A benchmark test suite for evolutionary multi-objective multi-concept optimization. Swarm Evol. Comput. 84: 101429 (2024) - [c84]Ankur Sinha, Dhaval Pujara, Hemant Kumar Singh:
Decomposition of Difficulties in Complex Optimization Problems using a Bilevel Approach. CEC 2024: 1-8 - [c83]Bing Wang, Hemant Kumar Singh, Tapabrata Ray:
Improving the Performance of Bilevel Evolutionary Algorithms using Variable Associations. CEC 2024: 1-8 - [c82]Angus Kenny
A Hierarchical Dissimilarity Metric for Automated Machine Learning Pipelines, and Visualizing Search Behaviour. EvoApplications@EvoStar 2024: 115-129 - [c81]Frank Neumann
Evolutionary computation for stochastic problems. GECCO Companion 2024: 1352-1368 - [c80]Angus Kenny
Using Bayesian Optimization to Improve Hyperparameter Search in TPOT. GECCO 2024 - [c79]Kamrul Hasan Rahi
Towards solving expensive optimization problems with heterogeneous constraint costs. GECCO Companion 2024: 2032-2040 - [i5]Ankur Sinha, Dhaval Pujara, Hemant Kumar Singh:
Decomposition of Difficulties in Complex Optimization Problems Using a Bilevel Approach. CoRR abs/2407.03454 (2024) - [i4]Bing Wang, Hemant K. Singh, Tapabrata Ray:
Pareto Set Prediction Assisted Bilevel Multi-objective Optimization. CoRR abs/2409.03328 (2024) - 2023
- [j31]Angus Kenny
An Iterative Two-Stage Multifidelity Optimization Algorithm for Computationally Expensive Problems. IEEE Trans. Evol. Comput. 27(3): 520-534 (2023) - [j30]Kamrul Hasan Rahi
A Steady-State Algorithm for Solving Expensive Multiobjective Optimization Problems With Nonparallelizable Evaluations. IEEE Trans. Evol. Comput. 27(5): 1544-1558 (2023) - [c78]Jing Liu, Hemant K. Singh, Saber M. Elsayed
Effective Robotic Swarm Shepherding in the Presence of Obstacles. CEC 2023: 1-8 - [c77]Kamrul Hasan Rahi
A Generalized Surrogate-Assisted Evolutionary Algorithm for Expensive Multi-Objective Optimization. CEC 2023: 1-8 - [c76]Bing Wang, Hemant Kumar Singh, Tapabrata Ray:
An Evaluation of Simple Solution Transfer Strategies for Bilevel Multiobjective Optimization. CEC 2023: 1-8 - [c75]Angus Kenny, Tapabrata Ray, Hemant Kumar Singh, Xiaodong Li:
A Test Suite for Multi-objective Multi-fidelity Optimization. EMO 2023: 361-373 - [c74]Angus Kenny
Hybridizing TPOT with Bayesian Optimization. GECCO 2023: 502-510 - [c73]Matthew Lette
Vertical-Axis Wind Turbine Design Using Surrogate-assisted Optimization with Physical Experiments In-loop. GECCO 2023: 1391-1399 - [c72]Frank Neumann
Evolutionary computation for stochastic problems. GECCO Companion 2023: 1463-1476 - [c71]Vedika Srivastava
A Comparative Study of Neural Style Transfer Models. ICIMMI 2023: 157:1-157:4 - [c70]Duy Tung Nguyen
Multi-agent Knowledge Transfer in a Society of Interpretable Neural Network Minds for Dynamic Context Formation in Swarm Shepherding. IJCNN 2023: 1-9 - [c69]Jing Liu, Hemant K. Singh, Saber M. Elsayed, Robert A. Hunjet, Hussein A. Abbass:
Distance Constrained Robotic Swarm Shepherding Based on Two-Phase Ant Colony Optimisation. SMC 2023: 5224-5230 - [c68]Rounak Saha Niloy
A Brief Review of Multi-Concept Multi-Objective Optimization Problems. SSCI 2023: 1511-1517 - [i3]Jing Liu, Hemant K. Singh, Saber M. Elsayed
Planning-assisted autonomous swarm shepherding with collision avoidance. CoRR abs/2301.10363 (2023) - 2022
- [j29]Hemant Kumar Singh
Investigating the Use of Linear Programming and Evolutionary Algorithms for Multi-Objective Electric Vehicle Charging Problem. IEEE Access 10: 115322-115337 (2022) - [j28]Tapabrata Ray, Hemant Kumar Singh
Towards identification of solutions of interest for multi-objective problems considering both objective and variable space information. Appl. Soft Comput. 119: 108505 (2022) - [j27]Mohammad Mohiuddin Mamun
An approach for computationally expensive multi-objective optimization problems with independently evaluable objectives. Swarm Evol. Comput. 75: 101146 (2022) - [j26]Mohammad Mohiuddin Mamun
A Multifidelity Approach for Bilevel Optimization With Limited Computing Budget. IEEE Trans. Evol. Comput. 26(2): 392-399 (2022) - [c67]Tapabrata Ray, Mohammad Mohiuddin Mamun, Hemant Kumar Singh
A Simple Evolutionary Algorithm for Multi-modal Multi-objective Optimization. CEC 2022: 1-8 - [c66]Bing Wang, Hemant Kumar Singh
Investigating Neighborhood Solution Transfer Schemes for Bilevel Optimization. CEC 2022: 1-8 - [c65]Quang Nhat Huynh, Hemant Kumar Singh
Discovery of implicit relationships from data using linear programming and mixed integer linear programming. GECCO Companion 2022: 558-561 - [c64]Hemant Kumar Singh
Identifying Stochastically Non-dominated Solutions Using Evolutionary Computation. PPSN (2) 2022: 193-206 - [c63]Quang Nhat Huynh, Hemant K. Singh, Tapabrata Ray, Akira Oyama:
Improved Genetic Programming for Symbolic Regression: Case Studies on Practical Applications. SSCI 2022: 1135-1142 - [i2]Tapabrata Ray, Mohammad Mohiuddin Mamun, Hemant Kumar Singh:
A Simple Evolutionary Algorithm for Multi-modal Multi-objective Optimization. CoRR abs/2201.06718 (2022) - 2021
- [j25]Kamrul Hasan Rahi
Feasibility-ratio based sequencing for computationally efficient constrained optimization. Swarm Evol. Comput. 62: 100850 (2021) - [j24]Kamrul Hasan Rahi
Partial Evaluation Strategies for Expensive Evolutionary Constrained Optimization. IEEE Trans. Evol. Comput. 25(6): 1103-1117 (2021) - [c62]Bing Wang, Hemant Kumar Singh
Comparing Expected Improvement and Kriging Believer for Expensive Bilevel Optimization. CEC 2021: 1635-1642 - [c61]Yi Chen, Hemant Kumar Singh
A Fast Converging Evolutionary Algorithm for Constrained Multiobjective Portfolio Optimization. EMO 2021: 283-295 - [c60]Bing Wang, Hemant Kumar Singh
Investigating Normalization Bounds for Hypervolume-Based Infill Criterion for Expensive Multiobjective Optimization. EMO 2021: 519-530 - [c59]Bing Wang, Hemant Kumar Singh
Bridging kriging believer and expected improvement using bump hunting for expensive black-box optimization. GECCO Companion 2021: 211-212 - [c58]Brandon Parker, Hemant Kumar Singh
Multi-objective optimization across multiple concepts: a case study on lattice structure design. GECCO 2021: 1035-1042 - [c57]Essam Soliman Debie, Hemant K. Singh
A Neuro-Evolution Approach to Shepherding Swarm Guidance in the Face of Uncertainty. SMC 2021: 2634-2641 - 2020
- [j23]Heba El-Fiqi
The Limits of Reactive Shepherding Approaches for Swarm Guidance. IEEE Access 8: 214658-214671 (2020) - [j22]Hemant Kumar Singh
Investigating the equivalence between PBI and AASF scalarization for multi-objective optimization. Swarm Evol. Comput. 53: 100630 (2020) - [j21]Hemant Kumar Singh
Understanding Hypervolume Behavior Theoretically for Benchmarking in Evolutionary Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 24(3): 603-610 (2020) - [c56]Tapabrata Ray, Hemant Kumar Singh
Online intensification of search around solutions of interest for multi/many-objective optimization. CEC 2020: 1-8 - [c55]Heba El-Fiqi
A preliminary study towards an improved shepherding model. GECCO Companion 2020: 75-76 - [c54]Kamrul Hasan Rahi
Expediting the convergence of evolutionary algorithms by identifying promising regions of the search space. GECCO Companion 2020: 201-202 - [c53]Ahsanul Habib, Kamrul Hasan Rahi
Wind-turbine design optimization using a many-objective evolutionary algorithm. GECCO Companion 2020: 267-268 - [c52]Saber M. Elsayed
Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution. SSCI 2020: 2194-2201 - [p1]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Many-Objective Optimization with Limited Computing Budget. High-Performance Simulation-Based Optimization 2020: 17-46 - [i1]Saber M. Elsayed, Hemant K. Singh, Essam Soliman Debie, Anthony Perry, Benjamin Campbell, Robert A. Hunjet, Hussein A. Abbass:
Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution. CoRR abs/2008.12639 (2020)
2010 – 2019
- 2019
- [j20]Raul Fernandez Rojas
Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey. IEEE Access 7: 33304-33328 (2019) - [j19]Ahsanul Habib
A multiple surrogate assisted multi/many-objective multi-fidelity evolutionary algorithm. Inf. Sci. 502: 537-557 (2019) - [j18]Shelvin Chand
Evolving heuristics for the resource constrained project scheduling problem with dynamic resource disruptions. Swarm Evol. Comput. 44: 897-912 (2019) - [j17]Hemant Kumar Singh
Nested evolutionary algorithms for computationally expensive bilevel optimization problems: Variants and their systematic analysis. Swarm Evol. Comput. 48: 329-344 (2019) - [j16]Shelvin Chand
Evolving rollout-justification based heuristics for resource constrained project scheduling problems. Swarm Evol. Comput. 50 (2019) - [j15]Hemant Kumar Singh
Distance-Based Subset Selection for Benchmarking in Evolutionary Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 23(5): 904-912 (2019) - [j14]Ahsanul Habib
A Multiple Surrogate Assisted Decomposition-Based Evolutionary Algorithm for Expensive Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 23(6): 1000-1014 (2019) - [c51]Shelvin Chand
Rollout based Heuristics for the Quantum Circuit Compilation Problem. CEC 2019: 974-981 - [c50]Kamrul Hasan Rahi
Investigating the use of sequencing and infeasibility driven strategies for constrained optimization. CEC 2019: 1642-1649 - [c49]Hemant K. Singh
Modulation of Force Vectors for Effective Shepherding of a Swarm: A Bi-Objective Approach. CEC 2019: 2941-2948 - [c48]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Optimum Wind Farm Layouts: A Many-Objective Perspective and Case Study. EMO 2019: 707-718 - [c47]Ahsanul Habib, Hemant Kumar Singh
A component-wise study of K-RVEA: observations and potential future developments. GECCO (Companion) 2019: 201-202 - [c46]Hemant Kumar Singh
A parametric investigation of PBI and AASF scalarizations. GECCO (Companion) 2019: 233-234 - [c45]Quang Nhat Huynh, Hemant Kumar Singh
Investigating the use of linear programming to solve implicit symbolic regression problems. GECCO (Companion) 2019: 344-345 - [c44]Hemant Kumar Singh
Identifying solutions of interest for practical many-objective problems using recursive expected marginal utility. GECCO (Companion) 2019: 1734-1741 - 2018
- [j13]Marwa Keshk
Automatic estimation of differential evolution parameters using Hidden Markov Models. Evol. Intell. 10(3-4): 77-93 (2018) - [j12]Shelvin Chand
On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems. Inf. Sci. 432: 146-163 (2018) - [j11]Md. Asafuddoula, Hemant Kumar Singh
An Enhanced Decomposition-Based Evolutionary Algorithm With Adaptive Reference Vectors. IEEE Trans. Cybern. 48(8): 2321-2334 (2018) - [j10]Quang Nhat Huynh
Genetic Programming With Mixed-Integer Linear Programming-Based Library Search. IEEE Trans. Evol. Comput. 22(5): 733-747 (2018) - [c43]Hemant Kumar Singh
Investigation of a Simple Distance Based Ranking Metric for Decomposition-Based Multi/Many-Objective Evolutionary Algorithms. Australasian Conference on Artificial Intelligence 2018: 384-396 - [c42]Tapabrata Ray, Ahsanul Habib, Hemant Kumar Singh
Uncovering Performance Envelopes Through Optimum Design of Tests. Australasian Conference on Artificial Intelligence 2018: 445-457 - [c41]Shelvin Chand
Team Selection Using Multi-/Many-Objective Optimization with Integer Linear Programming. CEC 2018: 1-8 - [c40]Md. Monjurul Islam, Hemant Kumar Singh
Efficient Global Optimization for Solving Computationally Expensive Bilevel Optimization Problems. CEC 2018: 1-8 - [c39]Zhichao Lu
Balancing Survival of Feasible and Infeasible Solutions in Constraint Evolutionary Optimization Algorithms. CEC 2018: 1-8 - 2017
- [j9]Md. Monjurul Islam, Hemant Kumar Singh
An Enhanced Memetic Algorithm for Single-Objective Bilevel Optimization Problems. Evol. Comput. 25(4) (2017) - [j8]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
An approach to generate comprehensive piecewise linear interpolation of pareto outcomes to aid decision making. J. Glob. Optim. 68(1): 71-93 (2017) - [j7]Md. Monjurul Islam, Hemant Kumar Singh
A Surrogate Assisted Approach for Single-Objective Bilevel Optimization. IEEE Trans. Evol. Comput. 21(5): 681-696 (2017) - [j6]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Bridging the Gap: Many-Objective Optimization and Informed Decision-Making. IEEE Trans. Evol. Comput. 21(5): 813-820 (2017) - [c38]Ahsanul Habib, Hemant Kumar Singh
A Batch Infill Strategy for Computationally Expensive Optimization Problems. ACALCI 2017: 74-85 - [c37]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Enhanced Pareto Interpolation Method to Aid Decision Making for Discontinuous Pareto Optimal Fronts. Australasian Conference on Artificial Intelligence 2017: 93-105 - [c36]Md. Monjurul Islam, Hemant Kumar Singh
Use of a Non-nested Formulation to Improve Search for Bilevel Optimization. Australasian Conference on Artificial Intelligence 2017: 106-118 - [c35]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Decomposition Based Evolutionary Algorithm with a Dual Set of reference vectors. CEC 2017: 105-112 - [c34]Shelvin Chand
A heuristic algorithm for solving resource constrained project scheduling problems. CEC 2017: 225-232 - [c33]Hanwei Zhang, Aimin Zhou, Guixu Zhang, Hemant Kumar Singh
Accelerating MOEA/D by Nelder-Mead method. CEC 2017: 976-983 - [c32]Hemant Kumar Singh
Improvement of Reference Points for Decomposition Based Multi-objective Evolutionary Algorithms. SEAL 2017: 284-296 - [e1]George Leu, Hemant Kumar Singh, Saber M. Elsayed
Intelligent and Evolutionary Systems - The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings. Springer 2017, ISBN 978-3-319-49048-9 [contents] - 2016
- [j5]Hemant Kumar Singh
Development of optimization methods to deal with current challenges in engineering design optimization. AI Commun. 29(1): 219-221 (2016) - [c31]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
A Study on Performance Metrics to Identify Solutions of Interest from a Trade-Off Set. ACALCI 2016: 66-77 - [c30]Md. Monjurul Islam, Hemant Kumar Singh
A Nested Differential Evolution Based Algorithm for Solving Multi-objective Bilevel Optimization Problems. ACALCI 2016: 101-112 - [c29]Hemant Kumar Singh
Use of Infeasible Solutions During Constrained Evolutionary Search: A Short Survey. ACALCI 2016: 193-205 - [c28]Shelvin Chand
Finding robust solutions for resource constrained project scheduling problems involving uncertainties. CEC 2016: 225-232 - [c27]Quang Nhat Huynh, Hemant Kumar Singh
Optimum redesign of scale-free networks with robustness and cost considerations. CEC 2016: 529-536 - [c26]Md. Monjurul Islam, Hemant Kumar Singh
A memetic algorithm for solving bilevel optimization problems with multiple followers. CEC 2016: 1901-1908 - [c25]Kalyan Shankar Bhattacharjee, Hemant Kumar Singh
Multiple surrogate assisted multiobjective optimization using improved pre-selection. CEC 2016: 4328-4335 - [c24]Ahsanul Habib, Hemant Kumar Singh
A multi-objective batch infill strategy for efficient global optimization. CEC 2016: 4336-4343 - [c23]Md. Asafuddoula, Hemant Kumar Singh
A CUDA Implementation of an Improved Decomposition Based Evolutionary Algorithm for Multi-Objective Optimization. GECCO (Companion) 2016: 71-72 - [c22]Quang Nhat Huynh, Hemant Kumar Singh
A Semantics based Symbolic Regression Framework for Mining Explicit and Implicit Equations from Data. GECCO (Companion) 2016: 103-104 - [c21]Ahsanul Habib, Hemant Kumar Singh
A study on the effectiveness of constraint handling schemes within Efficient Global Optimization framework. SSCI 2016: 1-8 - [c20]Quang Nhat Huynh, Hemant Kumar Singh
Improving Symbolic Regression through a semantics-driven framework. SSCI 2016: 1-8 - 2015
- [j4]Md. Asafuddoula, Hemant K. Singh
Six-Sigma Robust Design Optimization Using a Many-Objective Decomposition-Based Evolutionary Algorithm. IEEE Trans. Evol. Comput. 19(4): 490-507 (2015) - [c19]Md. Asafuddoula, Tapabrata Ray
Performance of a steady state quantum genetic algorithm for multi/many-objective engineering optimization problems. CEC 2015: 893-899 - [c18]Bing Wang, Hemant Kumar Singh
A multi-objective genetic programming approach to uncover explicit and implicit equations from data. CEC 2015: 1129-1136 - [c17]Md. Monjurul Islam, Hemant Kumar Singh
A Memetic Algorithm for solving single objective bilevel optimization problems. CEC 2015: 1643-1650 - [c16]Hemant K. Singh
Re-design for Robustness: An Approach Based on Many Objective Optimization. EMO (2) 2015: 343-357 - [c15]Md. Asafuddoula, Tapabrata Ray
Characterizing Pareto Front Approximations in Many-objective Optimization. GECCO 2015: 607-614 - 2014
- [c14]Min Liu, Hemant Kumar Singh
A benchmark generator for dynamic capacitated arc routing problems. IEEE Congress on Evolutionary Computation 2014: 579-586 - [c13]Min Liu, Hemant Kumar Singh
A memetic algorithm with a new split scheme for solving dynamic capacitated arc routing problems. IEEE Congress on Evolutionary Computation 2014: 595-602 - [c12]Hemant Kumar Singh
Solving problems with a mix of hard and soft constraints using modified infeasibility driven evolutionary algorithm (IDEA-M). IEEE Congress on Evolutionary Computation 2014: 983-990 - [c11]Hemant Kumar Singh
A hybrid surrogate based algorithm (HSBA) to solve computationally expensive optimization problems. IEEE Congress on Evolutionary Computation 2014: 1069-1075 - 2013
- [j3]Hemant Kumar Singh
Optimum Oil Production Planning Using Infeasibility Driven Evolutionary Algorithm. Evol. Comput. 21(1): 65-82 (2013) - 2011
- [j2]Hemant Kumar Singh
A Pareto Corner Search Evolutionary Algorithm and Dimensionality Reduction in Many-Objective Optimization Problems. IEEE Trans. Evol. Comput. 15(4): 539-556 (2011) - [c10]Hemant Kumar Singh
Performance of a hybrid EA-DE-memetic algorithm on CEC 2011 real world optimization problems. IEEE Congress on Evolutionary Computation 2011: 1322-1326 - 2010
- [j1]Hemant Kumar Singh
C-PSA: Constrained Pareto simulated annealing for constrained multi-objective optimization. Inf. Sci. 180(13): 2499-2513 (2010) - [c9]Hemant K. Singh
Performance of Infeasibility Empowered Memetic Algorithm (IEMA) on Engineering Design Problems. Australasian Conference on Artificial Intelligence 2010: 425-434 - [c8]Hemant Kumar Singh
Surrogate assisted Simulated Annealing (SASA) for constrained multi-objective optimization. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c7]Hemant Kumar Singh
Performance of infeasibility empowered memetic algorithm for CEC 2010 constrained optimization problems. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2009
- [c6]Hemant K. Singh
Performance of infeasibility driven evolutionary algorithm (IDEA) on constrained dynamic single objective optimization problems. IEEE Congress on Evolutionary Computation 2009: 3127-3134 - [c5]Hemant K. Singh
An improved secondary ranking for many objective optimization problems. GECCO 2009: 1837-1838 - 2008
- [c4]Hemant K. Singh
Infeasibility Driven Evolutionary Algorithm (IDEA) for Engineering Design Optimization. Australasian Conference on Artificial Intelligence 2008: 104-115 - [c3]Hemant K. Singh
A simulated annealing algorithm for constrained Multi-Objective Optimization. IEEE Congress on Evolutionary Computation 2008: 1655-1662 - [c2]Hemant K. Singh
A Simulated Annealing Algorithm for Single Objective Trans-Dimensional Optimization Problems. HIS 2008: 19-24 - [c1]Hemant K. Singh
A Study on the Performance of Substitute Distance Based Approaches for Evolutionary Many Objective Optimization. SEAL 2008: 401-410
Coauthor Index
[j32] [c83] [c82] [c80] [c79] [i4] [j31] [j30] [c77] [c76] [c75] [c74] [c73] [c68] [j29] [j28] [j27] [j26] [c67] [c66] [c65] [c63] [i2] [j25] [j24] [c62] [c61] [c60] [c59] [c58] [c56] [c54] [c53] [p1] [j19] [j18] [j17] [j16] [j15] [j14] [c51] [c50] [c48] [c47] [c45] [c44] [j12] [j11] [j10] [c43] [c42] [c41] [c40] [j9] [j8] [j7] [j6] [c38] [c37] [c36] [c35] [c34] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [j4] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [j3] [j2] [c10] [j1] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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