Prashant Palkar

About

I am an Assistant Professor in the Industrial Engineering and Operations Research group at the Department of Mechanical Engineering at Indian Institute of Technology (IIT) Delhi, India. Earlier, I was at the Chair of Discrete Mathematics, Optimization and Operations Research at the Institute of Mathematics, University of Augsburg, since April 01, 2021. During my PhD, I have primarily worked with Prof. Ashutosh Mahajan on theory and algorithms for Mixed-integer Nonlinear Programs. I also worked with Dr. Jeffrey Larson, Dr. Sven Leyffer and Dr. Stefan Wild (all three from Argonne National Laboratory) on Mixed-integer Derivative-free Optimization. One of my prime interests is to work on optimization solvers. I implement many of my research ideas in the open-source framework MINOTAUR. Prior to starting my PhD, I worked with Tata Steel Limited for about four years as a "Process Modelling and Visualization" expert in the long products business chain. I worked at multiple sites in Singapore, Thailand and India, collaborated with various clients and consultants for solving various optimization problems. I was also involved in designing and building end-to-end business software for users with embedded optimization algorithms and solvers, back-end databases and front-end GUIs.

Work

Indian Institute of Technology Delhi
|

Assistant Professor

India

University of Augsburg
|

Postdoctoral Researcher

Germany

Tata Steel
|

Senior Manager, Process Modelling and Visualisation

India

Education

Indian Institute of Technology Bombay
India

Research Scholar

Indian Institute of Technology Bombay
India

Master of Technology

Publications

Dynamic traffic assignment for electric vehicles

Published by

Transportation Research Part B: Methodological

Summary

journal-article

Linearization and Parallelization Schemes for Convex Mixed-Integer Nonlinear Optimization

Published by

Computational Optimization and Applications

Summary

journal-article

Dynamic Traffic Assignment for Electric Vehicles

Published by

22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems

Summary

conference-paper

Mitigating Anomalies in Parallel Branch-and-Bound Based Algorithms for Mixed-Integer Nonlinear Optimization

Published by

Lecture Notes in Computer Science

Summary

book-chapter

A method for convex black-box integer global optimization

Published by

Journal of Global Optimization

Summary

journal-article

A mathematical programming-and simulation-based framework to evaluate cyberinfrastructure design choices

Published by

2017 IEEE 13th International Conference on e-Science (e-Science)

Summary

conference-paper

A Branch-and-Estimate heuristic procedure for solving nonconvex integer optimization problems

Published by

2015 IEEE International Parallel and Distributed Processing Symposium Workshop

Summary

conference-paper