Papers Papers/2022 Papers Papers/2022



Paper Unlock

Authors: Rodrigo Lankaites Pinheiro 1 ; Dario Landa-Silva 1 ; Rong Qu 1 ; Edson Yanaga 2 and Ademir Aparecido Constantino 3

Affiliations: 1 University of Nottingham, United Kingdom ; 2 Unicesumar - Centro Universitário Cesumar, Brazil ; 3 Universidade Estadual de Maringá, Brazil

Keyword(s): Application Programming Interface, Workforce Scheduling and Routing Problems, Decision Support Systems, Research And Development.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Databases and Information Systems Integration ; Enterprise Information Systems ; Industrial Applications of Artificial Intelligence ; Operational Research ; Performance Evaluation and Benchmarking ; Problem Solving ; Scheduling and Planning

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. (More)


Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Pinheiro, R.; Landa-Silva, D.; Qu, R.; Yanaga, E. and Constantino, A. (2016). Towards an Efficient API for Optimisation Problems Data. In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-187-8; ISSN 2184-4992, SciTePress, pages 89-98. DOI: 10.5220/0005915800890098

author={Rodrigo Lankaites Pinheiro. and Dario Landa{-}Silva. and Rong Qu. and Edson Yanaga. and Ademir Aparecido Constantino.},
title={Towards an Efficient API for Optimisation Problems Data},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS},


JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Towards an Efficient API for Optimisation Problems Data
SN - 978-989-758-187-8
IS - 2184-4992
AU - Pinheiro, R.
AU - Landa-Silva, D.
AU - Qu, R.
AU - Yanaga, E.
AU - Constantino, A.
PY - 2016
SP - 89
EP - 98
DO - 10.5220/0005915800890098
PB - SciTePress