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

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Assistant Professor

India

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University of Augsburg

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Postdoctoral Researcher

Germany

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Tata Steel

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Senior Manager, Process Modelling and Visualisation

India

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Education

Indian Institute of Technology Bombay

India
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Research Scholar

Indian Institute of Technology Bombay

India
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Master of Technology

Publications

Dynamic traffic assignment for electric vehicles

Transportation Research Part B: Methodological

journal-article

Linearization and Parallelization Schemes for Convex Mixed-Integer Nonlinear Optimization

Computational Optimization and Applications

journal-article

Dynamic Traffic Assignment for Electric Vehicles

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

conference-paper

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

Lecture Notes in Computer Science

book-chapter

A method for convex black-box integer global optimization

Journal of Global Optimization

journal-article

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

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

conference-paper

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

2015 IEEE International Parallel and Distributed Processing Symposium Workshop

conference-paper