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Good Laboratory Practice for optimization research

Author

Listed:
  • Graham Kendall

    (University of Nottingham, Nottingham, UK
    University of Nottingham Malaysia Campus, Semenyih, Malaysia)

  • Ruibin Bai

    (University of Nottingham Ningbo, Ningbo, China)

  • Jacek Błazewicz

    (Poznan University of Technology, Poznan, Poland)

  • Patrick De Causmaecker

    (KU Leuven, Campus Kulak, Kortrijk, Belgium)

  • Michel Gendreau

    (University of Montreal, Montreal, Canada)

  • Robert John

    (University of Nottingham, Nottingham, UK)

  • Jiawei Li

    (University of Nottingham, Nottingham, UK)

  • Barry McCollum

    (Queen’s University Belfast, Belfast, UK)

  • Erwin Pesch

    (Universit&aauml;t Siegen, Siegen, Germany)

  • Rong Qu

    (University of Nottingham, Nottingham, UK)

  • Nasser Sabar

    (University of Nottingham Malaysia Campus, Semenyih, Malaysia)

  • Greet Vanden Berghe

    (KU Leuven, Technology Campus Gent, Gent, Belgium)

  • Angelina Yee

    (University of Nottingham Malaysia Campus, Semenyih, Malaysia)

Abstract

Good Laboratory Practice has been a part of non-clinical research for over 40 years. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin its research. In this paper we argue the need to adopt standards in optimization research. Building on previous papers, many of which have suggested that the optimization research community should adopt certain standards, we suggest a concrete set of recommendations that the community should adopt. We also discuss how the proposals in this paper could be progressed.

Suggested Citation

  • Graham Kendall & Ruibin Bai & Jacek Błazewicz & Patrick De Causmaecker & Michel Gendreau & Robert John & Jiawei Li & Barry McCollum & Erwin Pesch & Rong Qu & Nasser Sabar & Greet Vanden Berghe , 2016. "Good Laboratory Practice for optimization research," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 676-689, April.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:4:p:676-689
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    Citations

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    Cited by:

    1. Brownstone, David & McBride, Michael & Kong, Si-Yuan & Mahmassani, Amine, 2017. "Experimental Studies for Traffic Incident Management," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6kx670mv, Institute of Transportation Studies, UC Berkeley.
    2. Jann Michael Weinand & Kenneth Sorensen & Pablo San Segundo & Max Kleinebrahm & Russell McKenna, 2020. "Research trends in combinatorial optimisation," Papers 2012.01294, arXiv.org.
    3. Jeff Scales, 2020. "A design science research approach to closing the gap between the research and practice of project scheduling," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(5), pages 804-812, September.
    4. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    5. Rudabeh Meskarian & Marion L Penn & Sarah Williams & Thomas Monks, 2017. "A facility location model for analysis of current and future demand for sexual health services," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-18, August.
    6. Swan, Jerry & Adriaensen, Steven & Brownlee, Alexander E.I. & Hammond, Kevin & Johnson, Colin G. & Kheiri, Ahmed & Krawiec, Faustyna & Merelo, J.J. & Minku, Leandro L. & Özcan, Ender & Pappa, Gisele L, 2022. "Metaheuristics “In the Large”," European Journal of Operational Research, Elsevier, vol. 297(2), pages 393-406.
    7. Adam Sulich & Małgorzata Rutkowska, 2017. "Green jobs and changes in modern economy on the labour market," WORking papers in Management Science (WORMS) WORMS/17/03, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    8. Manerba, Daniele & Mansini, Renata & Riera-Ledesma, Jorge, 2017. "The Traveling Purchaser Problem and its variants," European Journal of Operational Research, Elsevier, vol. 259(1), pages 1-18.
    9. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
    10. Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.

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