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ORCIDPradyumn Kumar Shukla
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2020 – today
- 2022
[j6]Poonam Kesarwani, Pradyumn Kumar Shukla, Joydeep Dutta
, Kalyanmoy Deb:
Approximations for Pareto and Proper Pareto solutions and their KKT conditions. Math. Methods Oper. Res. 96(1): 123-148 (2022)
2010 – 2019
- 2019
- [j5]Deepak Sharma, Pradyumn Kumar Shukla:
Line-prioritized environmental selection and normalization scheme for many-objective optimization using reference-lines-based framework. Swarm Evol. Comput. 51 (2019) - 2017
- [c25]Marlon Alexander Braun, Pradyumn Kumar Shukla, Hartmut Schmeck:
Angle-Based Preference Models in Multi-objective Optimization. EMO 2017: 88-102 - [c24]Marlon Alexander Braun, Lars Heling, Pradyumn Kumar Shukla, Hartmut Schmeck:
Multimodal scalarized preferences in multi-objective optimization. GECCO 2017: 545-552 - 2016
- [j4]Marlon Alexander Braun, S. Seijo, Javier Echanobe, Pradyumn Kumar Shukla, Inés del Campo, Javier A. García-Sedano, Hartmut Schmeck:
A neuro-genetic approach for modeling and optimizing a complex cogeneration process. Appl. Soft Comput. 48: 347-358 (2016) - 2015
- [c23]Marlon Alexander Braun, Pradyumn Kumar Shukla, Hartmut Schmeck:
Obtaining Optimal Pareto Front Approximations using Scalarized Preference Information. GECCO 2015: 631-638 - 2014
- [c22]Pradyumn Kumar Shukla, Marlon Alexander Braun, Hartmut Schmeck:
On the interrelationships between knees and aggregate objective functions. GECCO (Companion) 2014: 95-96 - [c21]Pradyumn Kumar Shukla, Michael P. Cipold, Claus C. Bachmann, Hartmut Schmeck:
On homogenization of coal in longitudinal blending beds. GECCO 2014: 1199-1206 - [c20]Pradyumn Kumar Shukla, Nadja Doll, Hartmut Schmeck:
A theoretical analysis of volume based Pareto front approximations. GECCO 2014: 1415-1422 - 2013
- [c19]Pradyumn Kumar Shukla, Marlon Alexander Braun:
Indicator Based Search in Variable Orderings: Theory and Algorithms. EMO 2013: 66-80 - [c18]Michael Emmerich, André H. Deutz, Johannes W. Kruisselbrink, Pradyumn Kumar Shukla:
Cone-Based Hypervolume Indicators: Construction, Properties, and Efficient Computation. EMO 2013: 111-127 - [c17]Pradyumn Kumar Shukla, Marlon Alexander Braun, Hartmut Schmeck:
Theory and Algorithms for Finding Knees. EMO 2013: 156-170 - [c16]Pradyumn Kumar Shukla, Michael Emmerich, André H. Deutz:
A Theoretical Analysis of Curvature Based Preference Models. EMO 2013: 367-382 - 2012
- [c15]Florian Allerding, Marc Premm, Pradyumn Kumar Shukla, Hartmut Schmeck:
Electrical Load Management in Smart Homes Using Evolutionary Algorithms. EvoCOP 2012: 99-110 - [c14]Pradyumn Kumar Shukla, Christian Hirsch, Hartmut Schmeck:
Towards a Deeper Understanding of Trade-offs Using Multi-objective Evolutionary Algorithms. EvoApplications 2012: 396-405 - [c13]Michael P. Cipold, Pradyumn Kumar Shukla, Claus C. Bachmann, Kaibin Bao, Hartmut Schmeck:
An Evolutionary Optimization Approach for Bulk Material Blending Systems. PPSN (1) 2012: 478-488 - 2011
- [c12]Christian Hirsch, Pradyumn Kumar Shukla, Hartmut Schmeck:
Variable Preference Modeling Using Multi-Objective Evolutionary Algorithms. EMO 2011: 91-105 - [c11]Marlon Alexander Braun, Pradyumn Kumar Shukla, Hartmut Schmeck:
Preference Ranking Schemes in Multi-Objective Evolutionary Algorithms. EMO 2011: 226-240 - 2010
- [b1]Pradyumn Kumar Shukla:
Levenberg-Marquardt Algorithms for Nonlinear Equations, Multi-objective Optimization, and Complementarity Problems. University of Dresden, Germany, 2010 - [c10]Pradyumn Kumar Shukla:
On Modeling and Evolutionary Optimization of Nonlinearly Coupled Pedestrian Interactions. EvoApplications (1) 2010: 21-30 - [c9]Pradyumn Kumar Shukla, Christian Hirsch, Hartmut Schmeck:
A Framework for Incorporating Trade-Off Information Using Multi-Objective Evolutionary Algorithms. PPSN (2) 2010: 131-140 - [c8]Pradyumn Kumar Shukla, Christian Hirsch, Hartmut Schmeck:
In Search of Equitable Solutions Using Multi-objective Evolutionary Algorithms. PPSN (1) 2010: 687-696
2000 – 2009
- 2009
- [c7]Pradyumn Kumar Shukla:
Genetically Optimized Architectural Designs for Control of Pedestrian Crowds. ACAL 2009: 22-31 - 2008
- [j3]Andreas Fischer, Pradyumn Kumar Shukla:
A Levenberg-Marquardt algorithm for unconstrained multicriteria optimization. Oper. Res. Lett. 36(5): 643-646 (2008) - 2007
- [j2]Anders Johansson, Dirk Helbing, Pradyumn Kumar Shukla:
Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data. Adv. Complex Syst. 10(supp02): 271-288 (2007) - [j1]Pradyumn Kumar Shukla, Kalyanmoy Deb:
On finding multiple Pareto-optimal solutions using classical and evolutionary generating methods. Eur. J. Oper. Res. 181(3): 1630-1652 (2007) - [c6]Pradyumn Kumar Shukla:
On Gradient Based Local Search Methods in Unconstrained Evolutionary Multi-objective Optimization. EMO 2007: 96-110 - [c5]Pradyumn Kumar Shukla:
Exploiting Second Order Information in Computational Multi-objective Evolutionary Optimization. EPIA Workshops 2007: 271-282 - [c4]Pradyumn Kumar Shukla:
Gradient Based Stochastic Mutation Operators in Evolutionary Multi-objective Optimization. ICANNGA (1) 2007: 58-66 - [c3]Pradyumn Kumar Shukla:
On the Normal Boundary Intersection Method for Generation of Efficient Front. International Conference on Computational Science (1) 2007: 310-317 - [c2]Pradyumn Kumar Shukla:
In Search of Proper Pareto-optimal Solutions Using Multi-objective Evolutionary Algorithms. International Conference on Computational Science (4) 2007: 1013-1020 - 2005
- [c1]Pradyumn Kumar Shukla, Kalyanmoy Deb, Santosh Tiwari:
Comparing Classical Generating Methods with an Evolutionary Multi-objective Optimization Method. EMO 2005: 311-325 - [i1]Pradyumn Kumar Shukla, Joydeep Dutta, Kalyanmoy Deb:
On Properly Pareto Optimal Solutions. Practical Approaches to Multi-Objective Optimization 2005
Coauthor Index
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