An integrated platform for intuitive mathematical programming modeling using LaTeX

Triantafyllidis, Charalampos; Papageorgiou, Lazaros G.

doi:10.7717/peerj-cs.161

Cited by 5 publications

(4 citation statements)

References 27 publications

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“…Here, we provide an overview of how the RRB program at IRRI has leveraged in R computational power with open-source resource tools of R Markdown, plotly, LaTeX [ 6 ] ( https://www.latex-project.org/get/ ) and HTML to develop an analysis workflow of phenotypic data analysis, and re-designing it to a reproducible document for better interpretations, visualization and easy sharing with collaborators. The developed analysis workflow demonstrates how to pre-process and check data quality and perform robust data analysis using modern statistical tools and approaches.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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Background Developing a systematic phenotypic data analysis pipeline, creating enhanced visualizations, and interpreting the results is crucial to extract meaningful insights from data in making better breeding decisions. Here, we provide an overview of how the Rainfed Rice Breeding (RRB) program at IRRI has leveraged R computational power with open-source resource tools like R Markdown, plotly, LaTeX, and HTML to develop an open-source and end-to-end data analysis workflow and pipeline, and re-designed it to a reproducible document for better interpretations, visualizations and easy sharing with collaborators. Results We reported the state-of-the-art implementation of the phenotypic data analysis pipeline and workflow embedded into a well-descriptive document. The developed analytical pipeline is open-source, demonstrating how to analyze the phenotypic data in crop breeding programs with step-by-step instructions. The analysis pipeline shows how to pre-process and check the quality of phenotypic data, perform robust data analysis using modern statistical tools and approaches, and convert it into a reproducible document. Explanatory text with R codes, outputs either in text, tables, or graphics, and interpretation of results are integrated into the unified document. The analysis is highly reproducible and can be regenerated at any time. The analytical pipeline source codes and demo data are available at https://github.com/whussain2/Analysis-pipeline. Conclusion The analysis workflow and document presented are not limited to IRRI’s RRB program but are applicable to any organization or institute with full-fledged breeding programs. We believe this is a great initiative to modernize the data analysis of IRRI’s RRB program. Further, this pipeline can be easily implemented by plant breeders or researchers, helping and guiding them in analyzing the breeding trials data in the best possible way.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…We feel the need to continue research by further distilling the main gaps within the existing AMLs and proposing both a more generalized modeling language and an open-source-based tool combining the best characteristics of the existing AMLs. While a suggestion for using L A T E X as a foundation for the AML tool by Triantafyllidis and Papageorgiou [24] already exists, we believe another, more user-friendly alternative can be provided.…”

Section: Introductionmentioning

confidence: 99%

Web-Based Tool for Algebraic Modeling and Mathematical Optimization

Jusevičius

Paulavičius

2021

Mathematics

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In this article, we present a new open-source tool for algebraic modeling and mathematical optimization. We begin by distilling the main gaps within the existing algebraic modeling languages and tools (varying performance, limited cross-compatibility, complex syntax, and different solver, feature, and problem type support). Later, we propose a state-of-the-art web-based tool (WebAML and Optimization System) for algebraic modeling languages and mathematical optimization. The tool does not require specific algebraic language knowledge, allows solving problems using different solvers, and utilizes the best characteristics of existing algebraic modeling languages. We also provide clear extension points and ideas on how we could further improve such a tool.

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“…Linear Programming (LP) constitutes one of the most fundamental classes of mathematical programming models which is widely used in many scientific areas since many real world problems can be formulated as Linear Programs (LPs) (Triantafyllidis & Papageorgiou, 2018;Gkioulekas & Papageorgiou, 2019;Yang et al, 2016;Amin & Emrouznejad, 2011;Janssens & Ramaekers, 2011;Fernndez & Borrajo, 2012;Burdett et al, 2017). LP is an important tool nowadays in many applications, spanning across a broad spectrum of fields (Bertsimas & Tsitsiklis, 1997).…”

Section: Introductionmentioning

confidence: 99%

A new non-monotonic infeasible simplex-type algorithm for Linear Programming

Triantafyllidis

Samaras

2020

PeerJ Computer Science

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This paper presents a new simplex-type algorithm for Linear Programming with the following two main characteristics: (i) the algorithm computes basic solutions which are neither primal or dual feasible, nor monotonically improving and (ii) the sequence of these basic solutions is connected with a sequence of monotonically improving interior points to construct a feasible direction at each iteration. We compare the proposed algorithm with the state-of-the-art commercial CPLEX and Gurobi Primal-Simplex optimizers on a collection of 93 well known benchmarks. The results are promising, showing that the new algorithm competes versus the state-of-the-art solvers in the total number of iterations required to converge.

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An integrated platform for intuitive mathematical programming modeling using LaTeX

Cited by 5 publications

References 27 publications

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

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

Web-Based Tool for Algebraic Modeling and Mathematical Optimization

A new non-monotonic infeasible simplex-type algorithm for Linear Programming

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