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Towards an efficient API for optimisation problems data

Pinheiro, Rodrigo Lankaites; Landa-Silva, Dario; Qu, Rong; Yanaga, Edson; Constantino, Ademir Aparecido

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Authors

Rodrigo Lankaites Pinheiro

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DARIO LANDA SILVA DARIO.LANDASILVA@NOTTINGHAM.AC.UK
Professor of Computational Optimisation

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RONG QU rong.qu@nottingham.ac.uk
Professor of Computer Science

Edson Yanaga

Ademir Aparecido Constantino



Contributors

Slimane Hammoudi
Editor

Leszek Maciaszek
Editor

Michele M. Missikoff
Editor

Olivier Camp
Editor

Jos� Cordeiro
Editor

Abstract

The literature presents many application programming interfaces (APIs) and frameworks that provide state of the art algorithms and techniques for solving optimisation problems. The same cannot be said about APIs and frameworks focused on the problem data itself because with the peculiarities and details of each variant of a problem, it is virtually impossible to provide general tools that are broad enough to be useful on a large scale. However, there are benefits of employing problem-centred APIs in a R&D environment: improving the understanding of the problem, providing fairness on the results comparison, providing efficient data structures for different solving techniques, etc. Therefore, in this work we propose a novel design methodology for an API focused on an optimisation problem. Our methodology relies on a data parser to handle the problem specification files and on a set of efficient data structures to handle the information on memory, in an intuitive fashion for researchers and efficient for the solving algorithms. Also, we present the concepts of a solution dispenser that can manage solutions objects in memory better than built-in garbage collectors. Finally, we describe the positive results of employing a tailored API to a project involving the development of optimisation solutions for workforce scheduling and routing problems.

Citation

Pinheiro, R. L., Landa-Silva, D., Qu, R., Yanaga, E., & Constantino, A. A. (2016). Towards an efficient API for optimisation problems data. In . S. Hammoudi, . L. Maciaszek, . M. M. Missikoff, O. Camp, & . J. Cordeiro (Eds.), Proceedings of the 18th International Conference on Enterprise Information Systems . Volume 2: ICEIS (89-98). https://doi.org/10.5220/0005915800890098

Conference Name 18th International Conference on Enterprise Information Systems (ICEIS 2016)
Start Date Apr 25, 2016
End Date Apr 28, 2016
Acceptance Date Nov 15, 2015
Online Publication Date Apr 25, 2016
Publication Date Apr 25, 2016
Deposit Date Dec 7, 2016
Publicly Available Date Dec 7, 2016
Peer Reviewed Peer Reviewed
Pages 89-98
Book Title Proceedings of the 18th International Conference on Enterprise Information Systems . Volume 2: ICEIS
ISBN 978-989-758-187-8
DOI https://doi.org/10.5220/0005915800890098
Keywords application programming interface, workforce scheduling and routing problems, decision support systems, research and development
Public URL https://nottingham-repository.worktribe.com/output/775326
Publisher URL http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0005915800890098

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