Abstract
Throughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes.
Original language | English |
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Pages (from-to) | 423-617 |
Number of pages | 195 |
Journal | Journal of the Operational Research Society |
Volume | 75 |
Issue number | 3 |
Early online date | 27 Dec 2023 |
DOIs | |
Publication status | Published - 2024 |
Externally published | Yes |
Funding
Fotios Petropoulos would like to thank all the co-authors of this article for their very enthusiastic response and participation in this initiave. He is also indebted to his lead advisor for this project, Gilbert Laporte, as well as Christos Vasilakis, G\u00FCne\u015F Erdo\u011Fan, Stephen Disney and Maria Battarra for their help and suggestions. Finally, Fotios is grateful to John Boylan and the other Editors-in-Chief of the Journal of the Operational Research Society for inviting this paper to be part of the 75th issue of the journal. Fotios dedicates this article to Professor John Boylan: John, your kindness will always be remembered. Maria Battarra\u2019s work reported in this paper was undertaken as part of the Made Smarter Innovation: Centre for People-Led Digitalisation, at the University of Bath, University of Nottingham, and Loughborough University. David Canca\u2019s work was supported by the University of Sevilla, the Regional Government of Andalucia (Spain) and the European Regional Development Fund (ERDF) under grant US-1381656. Laurent Charlin and Andrea Lodi would like to thank Didier Ch\u00E9telat and Mizu Nishikawa-Toomey for reading and commenting on drafts of their subsection (\u00A72.1) and the CIFAR AI Chair and the CERC programs for funding. Salvatore Greco wishes to acknowledge the support of the Ministero dell\u2019Istruzione, dell\u2019Universita e dellaRicerca (MIUR) - PRIN 2017, project \u201CMultiple Criteria Decision Analysis and Multiple Criteria Decision Theory\u201D, grant 2017CY2NCA. Katherine Kent and Sam Rose thank Mithu Norris for the help and coordination with \u00A73.10 but also Emma Hickman and Ffion Lelii for their contribution. Silvano Martello, Paolo Toth and Daniele Vigo were supported by Air Force Office of Scientific Research under Grants no. FA8655-20-1-7012, FA8655-20-1-7019, FA9550-17-1-0234 and FA8655-21-1-7046. Dimitrios Sotiros\u2019s work was partially supported by the National Science Center (NCN, Poland) grant no. 2020/37/B/HS4/03125. Greet Vanden Berghe and Sanja Petrovic acknowledge the advice provided by Andrea Schaerf (University of Udine). Rafa\u0142 Weron\u2019s work was partially supported by the National Science Center (NCN, Poland) grant no. 2018/30/A/HS4/00444. David Canca\u2019s work was supported by the University of Sevilla, the Regional Government of Andalucia (Spain) and the European Regional Development Fund (ERDF) under grant US-1381656. The Office for National Statistics (ONS) played a vital role during the pandemic in monitoring infection rates. The Coronavirus (COVID-19) infection survey estimates how many people across England, Wales, Northern Ireland, and Scotland would have tested positive for a COVID-19 infection, regardless of whether they report experiencing symptoms. This study was a collaboration with academic partners and funded by Department of Health and Social Care. This major study involved asking people up and down the country to provide nose and throat swabs on a regular basis. These are analysed to see if they have contracted COVID-19. In addition, some adults are also asked to provide blood samples to determine what proportion of the population has antibodies to COVID-19. Further details of the methodology can be found in Office for National Statistics (). Laurent Charlin and Andrea Lodi would like to thank Didier Ch\u00E9telat and Mizu Nishikawa-Toomey for reading and commenting on drafts of their subsection (\u00A72.1) and the CIFAR AI Chair and the CERC programs for funding. Salvatore Greco wishes to acknowledge the support of the Ministero dell\u2019Istruzione, dell\u2019Universita e dellaRicerca (MIUR) - PRIN 2017, project \u201CMultiple Criteria Decision Analysis and Multiple Criteria Decision Theory\u201D, grant 2017CY2NCA. Dimitrios Sotiros\u2019s work was partially supported by the National Science Center (NCN, Poland) grant no. 2020/37/B/HS4/03125. Rafa\u0142 Weron\u2019s work was partially supported by the National Science Center (NCN, Poland) grant no. 2018/30/A/HS4/00444. Silvano Martello, Paolo Toth and Daniele Vigo were supported by Air Force Office of Scientific Research under Grants no. FA8655-20-1-7012, FA8655-20-1-7019, FA9550-17-1-0234 and FA8655-21-1-7046.
Funders | Funder number |
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Air Force Office of Scientific Research (AFOSR) | FA8655-20-1-7019, FA9550-17-1-0234, FA8655-20-1-7012, FA8655-21-1-7046 |
University of Seville | |
Ministero dell’Istruzione, dell’Università e della Ricerca | 2017CY2NCA |
Narodowe Centrum Nauki | 2018/30/A/HS4/00444, 2020/37/B/HS4/03125 |
European Regional Development Fund | US-1381656 |
Keywords
- decision making
- encyclopedia
- models
- optimisation
- practice
- principles
- programming
- Review
- simulation
- systems
- theory