| Literature DB >> 33816814 |
Charalampos P Triantafyllidis1,2, Lazaros G Papageorgiou1.
Abstract
This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work. ©2018 Triantafyllidis and Papageorgiou.Entities:
Keywords: Algebraic Modeling Languages; LaTeX; Mathematical programming; Optimization; Pyomo; Python
Year: 2018 PMID: 33816814 PMCID: PMC7924498 DOI: 10.7717/peerj-cs.161
Source DB: PubMed Journal: PeerJ Comput Sci ISSN: 2376-5992