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Experimental Analysis of Algebraic Modelling Languages for Mathematical Optimization
Volume 32, Issue 2 (2021), pp. 283–304
Pub. online: 23 March 2021      Type: Research Article      Open accessOpen Access
Received
1 October 2020
Accepted
1 March 2021
Published
23 March 2021

Abstract

In this work, we perform an extensive theoretical and experimental analysis of the characteristics of five of the most prominent algebraic modelling languages (AMPL, AIMMS, GAMS, JuMP, and Pyomo) and modelling systems supporting them. In our theoretical comparison, we evaluate how the reviewed modern algebraic modelling languages match the current requirements. In the experimental analysis, we use a purpose-built test model library to perform extensive benchmarks. We provide insights on which algebraic modelling languages performed the best and the features that we deem essential in the current mathematical optimization landscape. Finally, we highlight possible future research directions for this work.

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Biographies

Jusevičius Vaidas
vaidas.jusevicius@mif.vu.lt

V. Jusevičius received the master’s degree in software engineering from Vilnius University, Vilnius, Lithuania, in 2011. In 2017 he started PhD studies in computer science at Vilnius University, Institute of Data Science and Digital Technologies. His thesis title “Research and Development of an Open Source System for Algebraic Modeling Languages”. He is working as a partnership associate professor in Vilnius University, Institute of Computer Science, and as a Chief Software Architect for Danske Bank A/S.

Oberdieck Richard
https://orcid.org/0000-0002-8685-8694
oberdieck@gurobi.com

R. Oberdieck obtained his bachelor and MSc degrees from ETH Zurich in Switzerland (2009–1013), before pursuing a PhD in Chemical Engineering at Imperial College London, UK, which he completed in 2017. After using his knowledge in mathematical modelling and optimization in the space of renewable energies at the world leader in offshore wind energy, Ørsted A/S, he is now helping companies around the world to unlock business value through mathematical optimization as a Technical Account Manager for Gurobi Optimization, LLC.

Paulavičius Remigijus
https://orcid.org/0000-0003-2057-2922
remigijus.paulavicius@mif.vu.lt

R. Paulavičius received the PhD degree in computer science from Vytautas Magnus University, Kaunas, Lithuania, in 2010. He was a postdoctoral researcher with Vilnius University, Vilnius, Lithuania, and a research associate with Imperial College London, London, UK. He is currently a professor and the Head of the Blockchain Technologies Group, Institute of Data Science and Digital Technologies, Vilnius University. His research interests include optimization, distributed ledger technologies, parallel and distributed computing, machine learning, and the development and application of various operation research techniques.


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Keywords
algebraic modelling languages optimization AMPL AIMMS GAMS JuMP Pyomo

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