D.K. Saxena
Associate professor
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Interests
AI assisted Optimization, Evolutionary Multi- and Many-objective Optimization, Multi-Criteria Decision Making
dhish.saxena@me.iitr.ac.in
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01332286397
Biosketch
Educational Details
Professional Background
Administrative Positions

Research
Projects
Papers
Books
Collaborations

Honours and Awards
Honors
Memberships

Teaching Engagements
Teaching Engagements

Students
Supervisions
Associate Scholars

Miscellaneous
Events
Visits
Miscellaneous
BioSketch
Educational Details
IIT Kanpur
2008
PhD, Evolutionary Many-objective Optimization
Professional Background
Research Fellow (Liverhume)
01 Apr 2012 - 31 Jul 2012
Department of Computer Science, Bath University, UK
Academic Fellow
01 Jan 2008 - 31 Mar 2012
Manufacturing Department, Cranfield University, UK
Associate Professor
01 Apr 2016 - Present
Department of Mechanical & Industrial Engineering, IIT Roorkee
Administrative Positions
Associate Editor
01 Jan 2016 - Present
Elsevier's Swarm and Evolutionary Computation
Chief Warden KIH
01 Jul 2014 - 30 Jun 2016
IIT Roorkee
Member: Guest House Advisory Committee
01 Jan 2015 - 01 Jan 2017
IIT Roorkee
Member: Department Purchase Committee, under DOSW set-up
01 Jan 2015 - 01 Jan 2017
IIT Roorkee
Founding Co-ordinator, Tinkering Lab
01 Aug 2015 - 30 Jun 2016
IIT Roorkee
Research
Projects
TOPIC START DATE FIELD DESCRIPTION FINANCIAL OUTLAY FUNDING AGENCY OTHER OFFICERS
Networked Adaptive Traffic Signal Control in IoT-Enabled Smart Cities 20 Sep 2022 Smart Cities 53 Lakh INR National Science Foundation, USA and DST Sharon Di, Columbia University, USA
INNOVIZATION: Discovery of Innovative Knowledge through Optimization and Machine Learning 01 Apr 2019 INNOVIZATION: Discovery of Innovative Knowledge through Optimization and Machine Learning 105.64 Lakhs (USD 130,000) MHRD, GE (105.64 Lakhs: USD 130,000) Prof K Deb, MSU, USA
Decomposition Based Multiobjective Evolutionary Computation [Overseas-CI] 01 Jan 2015 Decomposition Based Multiobjective Evolutionary Computation [Overseas-CI] 800,000 RMB NSF, China (800,000 RMB)
Multi-objective Optimization of Composite Aircraft Wing. 01 Sep 2010 Multi-objective Optimization of Composite Aircraft Wing. 20000 GBP Airbus, UK Dr A.Tiwari
A Systems Approach towards Data Mining and Prediction in Airlines operations [PI] 01 Jan 2015 A Systems Approach towards Data Mining and Prediction in Airlines operations [PI] 483,000 Euro DeiTY-NWO-GE (483,000 Euro)
Founding Co-ordinator 01 Jan 2015 Tinkering Laboratory 2.5 crore INR (330,000 USD) MHRD (2.5 crore INR: 330,000 USD)
Many-objective Optimization: A way forward 01 Sep 2009 Many-objective Optimization: A way forward 80000 GBP Hewlett Packard, UK Dr A.Tiwari




Papers
A Localized High-Fidelity-Dominance based Many-Objective Evolutionary Algorithm
2022
D. K. Saxena, S. Mittal, S. Kapoor, and K. Deb | IEEE
Journal: IEEE Transactions on Evolutionary Computation
Enhanced Innovized Progress Operator for Evolutionary Multi-and Many-objective Optimization
2022
S. Mittal, D. K. Saxena, K. Deb and E. D. Goodman | IEEE: 10.1109/TEVC.2021.3131952.
Journal: IEEE Transactions on Evolutionary Computation
A Learning-based Innovized Progress Operator for Faster Convergence in Evolutionary Multi-objective Optimization
2022
S. Mittal, D.K. Saxena, K. Deb, and E.D. Goodman | ACM: https://doi.org/10.1145/3474059)
Journal: ACM Transactions on Evolutionary Learning and Optimization Pages: , 1-29 Volumes: , 2
Online summarization of dynamic graphs using subjective interestingness for sequential data
2021
S. Kapoor, D.K. Saxena and M. van Leeuwen | Springer
Journal: Data Mining and Knowledge Discovery Pages: , 88-126 Volumes: , 35
Discovering Subjectively Interesting Multigraph Patterns
2020
S. Kapoor, D.K. Saxena and M. van Leeuwen | Springer
Journal: Machine Learning Volumes: , 109
A new replica placement strategy based on multi-objective optimisation for HDFS
2020
Y. Li, M. Tian, Y. Wang, Q. Zhang, D. K. Saxena, and L. Jiao | Inderscience
Journal: International Journal of Bio-Inspired Computation Pages: , 13-22 Volumes: , 16
On Timing the Nadir-Point Estimation and/or Termination of Reference-Based Multi- and Many-objective Evolutionary Algorithms
2019
D. K. Saxena and Sarang Kapoor | Springer
Journal: Evolutionary Multi-Criterion Optimization Pages: , 191-202
Timing the Decision Support for Real-World Many-Objective Optimization Problems
2017
J. A Duro and D. K. Saxena | Springer
Journal: Evolutionary Multi-Criterion Optimization Pages: , 191-205
Entropy based Termination Criterion for Multiobjective Evolutionary Optimisation
2016
D. K. Saxena, Arnab Sinha, J. A. Duro and Q. Zhang | IEEE
Journal: IEEE Transactions on Evolutionary Computation Pages: , 485-498 Volumes: , 20
Machine learning based decision support for many-objective optimization problems
2014
J.A.Duro, D. K.Saxena, K.Deb and Q.Zhang | Elsevier
Journal: Neurocomputing Pages: , 30-47 Volumes: , 146
Identifying the Redundant and Ranking the Critical Constraints in Practical Optimization Problems
2013
D.K.Saxena, A.Rubino, J.A.Duro and A.Tiwari | Taylor & Francis
Journal: Engineering Optimization Pages: , 787-809 Volumes: , 45
Using Objective Reduction and Interactive Procedure to Handle Many-objective optimization Problems
2013
A.Sinha, D.K.Saxena, K.Deb and A.Tiwari | Elsevier
Journal: Applied Soft Computing Pages: , 415-427 Volumes: , 3
Objective Reduction in Many-objective Optimization: Linear and Nonlinear Algorithms
2012
D. K.Saxena, J.A.Duro, A.Tiwari, K.Deb and Q.Zhang | IEEE
Journal: IEEE Transactions on Evolutionary Computation Pages: , 1-23 Volumes: , 99
An Evolutionary Multi-objective Framework for Business Process Optimization
2012
K.Vergidis, D.K.Saxena and A.Tiwari | Elsevier
Journal: Applied Soft Computing Pages: , 2638-2653
Framework for Many-objective Test Problems with both Simple and Complicated Pareto-set Shapes
2011
D.K.Saxena, Q.Zhang, J.A.Duro and A.Tiwari | Springer
Journal: Evolutionary Multi-Criterion optimization Pages: , 197-211
On Handling a Large Number of Objectives A Posteriori and During Optimization
2008
D.Brockhoff, D.K.Saxena, K.Deb and E.Zitzler | Springer
Journal: Multi-objective Problem Solving from Nature Pages: , 377-403 Volumes: , 4
Non-linear Dimensionality Reduction Procedures for certain Large-dimensional Multi-objective Optimization Problems: Employing Correntropy and a Novel Maximum Variance Unfolding
2007
D.K.Saxena and K.Deb | Springer
Journal: Evolutionary Multi-Criterion Optimization Pages: , 772-787
Honors And Awards
Honors
Cranfield University
2011
MCDM Doctoral Award Finalist (one of the top 3 Ph.Ds internationally during 5 years period (2007-11)
MemberShips
IEEE
31 Aug 2020 - Present
Member
Elsevier: Swarm and Evolutionary Computation Journal
31 Aug 2020 - Present
Associate Editor
Students
SuperVisions
INNOVIZATION: Discovery of Innovative Knowledge through Optimization and Machine Learning
01 Jan 2018 - Present
Other Supervisors: , Scholar: Sukrit Mittal
Airline Crew Pairing Optimization
01 Aug 2015 - 04 Aug 2021
Other Supervisors: , Scholar: Divyam Agarwal
Subjectively Interesting Patterns in Networks
01 Aug 2015 - 14 Jun 2021
Other Supervisors: Dr. Siegfried Nijssen, Leiden University, Netherlands, Scholar: Sarang Kapoor
Machine Learning based Decision Support for a Class of Many-objective Optimization Problems
01 Jan 2009 - 30 Dec 2012
Other Supervisors: Dr Dhish K Saxena, Dr A.Tiwari, Scholar: Joao A Duro
Miscellaneous
Events
Designed & Conducted: Multidisciplinary Optimization: From Theory to Practice
01 Apr 2010 - 31 Mar 2012
Cranfield University & EnginSoft, UK
Self appraisal
- Dhish obtained his Ph.D in Evolutionary Many-objective Optimization (2008), under the supervision of Shanti Swaroop Bhatnagar Awardee Prof. Kalyanmoy Deb, IIT Kanpur. In MCDM Conference, Finland, 2011, Dhish's Ph.d was adjudged as one of the three most impactful Ph.Ds in the world, during 2007-11, in the area of Evolutionary Multi-objective Optimization and Multi-criterion Decision Making. Dhish brings on board his work-experience in the United Kingdom, for almost half-a-decade, where he worked with universities like Cranfield and Bath, in collaboration with companies like British Aerospace Systems, Hewlett Packard, and Airbus. The focus of his research has been two fold. At a fundamental level, his research has focused on facilitating a better understanding of highly constrained practical optimization problems, characterized by high degree of non-linearity and several (many) conflicting objectives. In that, machine learning techniques have been integrated with evolutionary algorithms to rank the objectives and also the constraints by order of their importance, to facilitate a decision support for a given problem. At the applied level, his research focus has been on demonstrating the utility of the self-developed tools and techniques on a wide range of real-world: engineering design, business-process, and multi-disciplinary optimization & multi-criterion decision making problems.
Publications

Patent Filed: D. Aggarwal, D.K. Saxena, T. Bäck, M. Emmerich, Crew Optimization, Netherlands Patent Application N2025010, Feb. 2020

[1] Enhanced Innovized Progress Operator for Evolutionary Multi-and Many-objective Optimization, S. Mittal, D. K. Saxena, K. Deb and E. D. Goodman, IEEE Transactions on Evolutionary Computation, 2022, doi: 10.1109/TEVC.2021.3131952.

[2] A Learning-based Innovized Progress Operator for Faster Convergence in Evolutionary Multi-objective Optimization, S. Mittal, D.K. Saxena, K. Deb, and E.D. Goodman; ACM Transactions on Evolutionary Learning and Optimization, 2022, Volume 2, Issue 1, 1-29 (https://doi.org/10.1145/3474059)

[3] Online summarization of dynamic graphs using subjective interestingness for sequential data, S. Kapoor, D. K. Saxena, and  M. van Leeuwen, Data Mining and Knowledge Discovery, 35, 88–126, 2021, https://doi.org/10.1007/s10618-020-00714-8

[4] Discovering Subjectively Interesting Multigraph Patterns, S. Kapoor, D.K. Saxena and M. van Leeuwen;Machine Learning, Vol 109, 2020: https://doi.org/10.1007/s10994-020-05873-9

[5] A new replica placement strategy based on multi-objective optimisation for HDFS; Y. Li, M. Tian, Y. Wang, Q. Zhang, D. K. Saxena, and L. Jiao; International Journal of Bio-Inspired Computation, 16(1), 2020, 13-22

[6] On Timing the Nadir-Point Estimation and/or Termination of Reference-Based Multi- and Many-objective Evolutionary Algorithms; D. K. Saxena and Sarang Kapoor; Evolutionary Multi-Criterion Optimization, 191-202, 2019.

[7] Timing the Decision Support for Real-World Many-Objective Optimization Problems; J. A Duro, D. K. Saxena; Evolutionary Multi-Criterion Optimization, 191-205, 2017.

[8] Entropy based Termination Criterion for Multiobjective Evolutionary Optimisation; D. K. Saxena, Arnab Sinha, J. A. Duro and Q. Zhang; IEEE Transactions on Evolutionary Computation, 20 (4), 485-498, 2016 Code

[9] Machine learning based decision support for many-objective optimization problems; J.A.Duro, D. K.Saxena, K.Deb and Q.Zhang; Neurocomputing, Volume 146, Pages 30–47. http://www.sciencedirect.com/science/article/pii/S0925231214008753

[10] Objective Reduction in Many-objective Optimization: Linear and Nonlinear Algorithms; D. K.Saxena, J.A.Duro, A.Tiwari, K.Deb and Q.Zhang; IEEE Transactions on Evolutionary Computation, 2012, 99, 1-23. Code

[11] An Evolutionary Multi-objective Framework for Business Process Optimization; K.Vergidis, D.K.Saxena and A.Tiwari; Applied Soft Computing, 2012, 2638-2653.

[12] Identifying the Redundant and Ranking the Critical Constraints in Practical Optimization Problems; D.K.Saxena, A.Rubino, J.A.Duro and A.Tiwari; Engineering Optimization, 2012, 1-23.

[13] Using Objective Reduction and Interactive Procedure to Handle Many-objective optimization Problems; A.Sinha, D.K.Saxena, K.Deb and A.Tiwari, Applied Soft Computing, 2013, 3(1), 415-427.

[14] Framework for Many-objective Test Problems with both Simple and Complicated Pareto-set Shapes; D.K.Saxena, Q.Zhang, J.A.Duro and A.Tiwari; Evolutionary Multi-Criterion optimization, 2011, 197-211.

[15] On Handling a Large Number of Objectives A Posteriori and During Optimization; D.Brockhoff, D.K.Saxena, K.Deb and E.Zitzler; Multi-objective Problem Solving from Nature, 2008, 4, 377-403.

[16] Non-linear Dimensionality Reduction Procedures for certain Large-dimensional Multi-objective Optimization Problems: Employing Correntropy and a Novel Maximum Variance Unfolding; D.K.Saxena and K.Deb; Evolutionary Multi-Criterion Optimization, 2007, 772-787.

Refereed Conference Papers

[1] A Generic and Computationally Efficient Automated Innovization Method for Power-Law Design Rules; K. Garg, A. Mukherjee, S. Mittal, D. K. Saxena and K. Deb; Genetic and Evolutionary Computation Conference Companion (GECCO ’20 Companion), July 8–12, 2020, Cancún, Mexico. ACM, New York, NY, USA: https://doi.org/10.1145/3377929.3390022

[2] Learning based Multi-objective Optimization Through ANN-Assisted Online Innovization; S. Mittal, D. K. Saxena and K. Deb; In Genetic and Evolutionary Computation Conference Companion (GECCO ’20 Companion), July 8–12, 2020, Cancún, Mexico. ACM, New York, NY, USA: https://doi.org/10.1145/3377929.3389925

[3] A Unified Automated Innovization Framework Using Threshold-based Clustering; S. Mittal, D. K. Saxena and K. Deb; Proceedings of Congress on Evolutionary Computation (CEC-2020), Piscataway, NJ: IEEE Press.

[4] Service Information in the Provision of Support Service Solutions: A State-of-the-art Review;   S. Kundu, A. McKay, R. Cuthbert, D. McFarlane, D. K. Saxena, A. Tiwari and P. Johnson;  CIRP  Industrial Product-Service Systems; Cranfield, U.K, 2009, ISBN: 978-0-9557436-5-8, 100-106.

[5] Constrained many-objective optimization: A way forward; D. K. Saxena, T. Ray, K. Deb and A. Tiwari; IEEE Congress on Evolutionary Computation, Trondheim, Norway, 2009, ISBN:978-1-4244-2958-5, 545-552.

[6] Dimensionality Reduction of Objectives and Constraints in multi-objective optimization problems: A system design perspective; D. K. Saxena and K. Deb; IEEE Congress on Evolutionary Computation, Hongkong, 2008, ISBN:978-1-4244-1822-0, 3204-3211.

[7] Trading on infeasibility by exploiting constraint’s criticality through multi-objectivization: A system design perspective; D. K. Saxena and K. Deb; IEEE Congress on Evolutionary Computation, Singapore,  2007, ISBN:978-1-4244-1339-3, 919-926.

[8] Searching for Pareto-optimal Solutions through Dimensionality Reduction for Certain Large-dimensional Multi-Objective Optimization Problems; K. Deb and D.K.Saxena; IEEE Congress on Evolutionary Computation, Vancouvar, Canada,  2006, IEEE: 0-7803-9487-9, 3353-3360.

Deliverables to "British Aerospace Systems & Engineering and Physical Sciences Research Council, UK"

for the project: "S4T : Support Service Solutions: Strategy and Transition"

Sr
No
Deliverable Year Pages Co-authors
No. Affiliation
1 Current state of service information 2008 31 5 University of - Leeds, Cranfield,  & Cambridge, UK.
2 Service information requirements 2009 43 6 University of - Cranfield,  Cambridge, & Leeds, UK.
3 Blueprint for future service information 2009 37 5 University of - Leeds, Cranfield,  & Cambridge, UK.
4

 Industrial case studies

2009 30 5 University of - Cranfield,  Cambridge, & Leeds, UK.
5 A roadmap for the transition to future service information solutions 009 11 10 University of -  Cambridge, Leeds, Cranfield, & BAES, UK.

 

Technical Reports

[2020]

[1] Aggarwal, D., Saxena, D.K., Bäck, T., Emmerich, M. (March, 2020). AirCROP: Airline Crew Pairing Optimizer for Complex Flight Networks Involving Multiple Crew Bases & Billion-Plus Variables. EADAL Report Number 2020001. [pdfNEW

[2] Aggarwal, D., Saxena, D.K., Bäck, T., Emmerich, M. (March, 2020). On Initializing Airline Crew Pairing Optimization for Large-scale Complex Flight NetworksEADAL Report Number 2020002. [pdfNEW

[2019]

[1] Aggarwal, D., Saxena, D.K., Bäck, T., Emmerich, M. (July, 2019). Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method. EADAL Report Number 2019001. [pdf]