Literature DB >> 33816814

An integrated platform for intuitive mathematical programming modeling using LaTeX.

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


  4 in total

1.  Opinion: Reproducible research can still be wrong: adopting a prevention approach.

Authors:  Jeffrey T Leek; Roger D Peng
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-10       Impact factor: 11.205

2.  Software with impact.

Authors: 
Journal:  Nat Methods       Date:  2014-03       Impact factor: 28.547

3.  Identifying drug effects via pathway alterations using an integer linear programming optimization formulation on phosphoproteomic data.

Authors:  Alexander Mitsos; Ioannis N Melas; Paraskeuas Siminelakis; Aikaterini D Chairakaki; Julio Saez-Rodriguez; Leonidas G Alexopoulos
Journal:  PLoS Comput Biol       Date:  2009-12-04       Impact factor: 4.475

4.  Detecting and removing inconsistencies between experimental data and signaling network topologies using integer linear programming on interaction graphs.

Authors:  Ioannis N Melas; Regina Samaga; Leonidas G Alexopoulos; Steffen Klamt
Journal:  PLoS Comput Biol       Date:  2013-09-05       Impact factor: 4.475

  4 in total
  1 in total

1.  Open-source analytical pipeline for robust data analysis, visualizations and sharing in crop breeding.

Authors:  Waseem Hussain; Mahender Anumalla; Margaret Catolos; Apurva Khanna; Ma Teresa Sta Cruz; Joie Ramos; Sankalp Bhosale
Journal:  Plant Methods       Date:  2022-02-05       Impact factor: 4.993

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.