| Data mining methods for knowledge discovery in multi-objective optimization: Part A-Survey S Bandaru, AHC Ng, K Deb Expert Systems with Applications 70, 139-159, 2017 | 192 | 2017 |
| Data mining methods for knowledge discovery in multi-objective optimization: Part B - New developments and applications S Bandaru, AHC Ng, K Deb Expert Systems with Applications 70, 119-138, 2017 | 192* | 2017 |
| An integrated approach to automated innovization for discovering useful design principles: Case studies from engineering K Deb, S Bandaru, D Greiner, A Gaspar-Cunha, CC Tutum Applied Soft Computing 15, 42-56, 2014 | 73 | 2014 |
| Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique S Bandaru, K Deb Engineering optimization 43 (9), 911-941, 2011 | 73 | 2011 |
| Metaheuristic techniques S Bandaru, K Deb Decision sciences, 693-750, 2016 | 54 | 2016 |
| A parameterless-niching-assisted bi-objective approach to multimodal optimization S Bandaru, K Deb 2013 IEEE congress on evolutionary computation, 95-102, 2013 | 52 | 2013 |
| Generating well-spaced points on a unit simplex for evolutionary many-objective optimization J Blank, K Deb, Y Dhebar, S Bandaru, H Seada IEEE Transactions on Evolutionary Computation 25 (1), 48-60, 2020 | 46 | 2020 |
| Automated discovery of vital knowledge from Pareto-optimal solutions: First results from engineering design S Bandaru, K Deb Ieee congress on evolutionary computation, 1-8, 2010 | 45 | 2010 |
| Decision sciences: theory and practice RN Sengupta, A Gupta, J Dutta Crc Press, 2016 | 43 | 2016 |
| Automated innovization for simultaneous discovery of multiple rules in bi-objective problems S Bandaru, K Deb Evolutionary Multi-Criterion Optimization: 6th International Conference, EMO …, 2011 | 41 | 2011 |
| On the performance of classification algorithms for learning Pareto-dominance relations S Bandaru, AHC Ng, K Deb 2014 IEEE Congress on evolutionary computation (CEC), 1139-1146, 2014 | 39 | 2014 |
| Modified SBX and adaptive mutation for real world single objective optimization S Bandaru, R Tulshyan, K Deb 2011 IEEE Congress of Evolutionary Computation (CEC), 1335-1342, 2011 | 35 | 2011 |
| Parameter tuned CMA-ES on the CEC'15 expensive problems M Andersson, S Bandaru, AHC Ng, A Syberfeldt 2015 IEEE congress on evolutionary computation (CEC), 1950-1957, 2015 | 34 | 2015 |
| Non-uniform mapping in real-coded genetic algorithms D Yashesh, K Deb, S Bandaru 2014 IEEE congress on evolutionary computation (CEC), 2237-2244, 2014 | 31 | 2014 |
| Generalized higher-level automated innovization with application to inventory management S Bandaru, T Aslam, AHC Ng, K Deb European Journal of Operational Research 243 (2), 480-496, 2015 | 28 | 2015 |
| Development, analysis and applications of a quantitative methodology for assessing customer satisfaction using evolutionary optimization S Bandaru, A Gaur, K Deb, V Khare, R Chougule, P Bandyopadhyay Applied Soft Computing 30, 265-278, 2015 | 26 | 2015 |
| Higher and lower-level knowledge discovery from Pareto-optimal sets S Bandaru, K Deb Journal of Global Optimization 57, 281-298, 2013 | 24 | 2013 |
| Innovative design and analysis of production systems by multi-objective optimization and data mining AHC Ng, S Bandaru, M Frantzén Procedia Cirp 50, 665-671, 2016 | 23 | 2016 |
| Radial basis functions with a priori bias as surrogate models: A comparative study K Amouzgar, S Bandaru, AHC Ng Engineering Applications of Artificial Intelligence 71, 28-44, 2018 | 20 | 2018 |
| A dimensionally-aware genetic programming architecture for automated innovization S Bandaru, K Deb Evolutionary Multi-Criterion Optimization: 7th International Conference, EMO …, 2013 | 20 | 2013 |
Kalyanmoy DebKoenig Endowed Chair Professor, Electrical and Computer Engineering, Michigan State UniversityVerified email at egr.msu.edu
