Multiple criteria model for allocating new medical robotic devices to treatment centres

Jones, Dylan; Firouzy, Sina; Labib, Ashraf; Argyriou, Athanasios V.

doi:10.1016/j.ejor.2021.06.003

European Journal of Operational Research

2022

DOI: 10.1016/j.ejor.2021.06.003

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Multiple criteria model for allocating new medical robotic devices to treatment centres

Dylan Jones

Sina Firouzy

Ashraf Labib

et al.

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Cited by 5 publications

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“…Literature review. For multicriteria scheduling, we refer the reader to the surveys [8,13,7], and to the recent results [9,5,11,2,6]. Here we only mention the results closely related to uniform machine scheduling.…”

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confidence: 99%

Faster algorithms for bicriteria scheduling of identical jobs on uniform machines

Shen

Liang

2023

JIMO

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<p style='text-indent:20px;'>This paper studies the problem of scheduling <inline-formula><tex-math id="M1">\begin{document}$ n $\end{document}</tex-math></inline-formula> jobs with equal processing times on <inline-formula><tex-math id="M2">\begin{document}$ m $\end{document}</tex-math></inline-formula> uniform machines to optimize two criteria simultaneously. The main contribution is an <inline-formula><tex-math id="M3">\begin{document}$ O(n\log m+n^3) $\end{document}</tex-math></inline-formula>-time algorithm for two general min-max criteria, improving the previous <inline-formula><tex-math id="M4">\begin{document}$ O(n\log m+n^4) $\end{document}</tex-math></inline-formula> time complexity. For a particular min-sum criterion (total weighted completion time or total tardiness) in combination with a general min-max criterion, <inline-formula><tex-math id="M5">\begin{document}$ O(n\log m+n^3) $\end{document}</tex-math></inline-formula>-time algorithms are also obtained, improving the previous <inline-formula><tex-math id="M6">\begin{document}$ O(n\log m+n^3\log n) $\end{document}</tex-math></inline-formula> time complexity. The algorithms can produce all Pareto optimal points together with the corresponding schedules.</p>

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mentioning

confidence: 99%

Faster algorithms for bicriteria scheduling of identical jobs on uniform machines

Shen

Liang

2023

JIMO

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Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series

Dai,

Cerqueti,

Wang

et al. 2023

Ann Oper Res

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Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

Mohseny-Tonekabony,

Sadjadi,

Mohammadi

et al. 2024

Ann Oper Res

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This study presents a two-phase approach of Data Envelopment Analysis (DEA) and Goal Programming (GP) for portfolio selection, representing a pioneering attempt at combining these techniques within the context of portfolio selection. The approach expands on the conventional risk and return framework by incorporating additional financial factors and addressing data uncertainty, which allows for a thorough examination of portfolio outcomes while accommodating investor preferences and conservatism levels. The initial phase employs a super-efficiency DEA model to streamline asset selection by identifying suitable investment candidates based on efficiency scores, setting the stage for subsequent portfolio optimization. The second phase leverages the Extended GP (EGP) framework, which facilitates the comprehensive incorporation of investor preferences to determine the optimal weights of the efficient assets previously identified within the portfolio. Each goal is tailored to reflect specific financial factors spanning both technical and fundamental aspects. To tackle data uncertainty, robust optimization is applied. The research contributes to the robust GP (RGP) literature by analyzing new RGP variants, overcoming limitations of traditional and other uncertain GP models by incorporating uncertainty sets. Robust counterparts of the EGP models are accordingly developed using polyhedral and combined interval and polyhedral uncertainty sets, providing a flexible representation of uncertainty in financial markets. Empirical results, based on real data from the Tehran Stock Exchange comprising 779 assets, demonstrate the superiority of the proposed approach over traditional portfolio selection methods across various uncertainty settings. Additionally, a comprehensive sensitivity analysis investigates the impact of uncertainty levels on the robust EGP models. The proposed framework offers guidance to investors and fund managers through a pragmatic approach, enabling informed and robust portfolio decisions by considering efficiency, uncertainty, and extended financial factors.

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Multiple criteria model for allocating new medical robotic devices to treatment centres

Cited by 5 publications

References 29 publications

Faster algorithms for bicriteria scheduling of identical jobs on uniform machines

Faster algorithms for bicriteria scheduling of identical jobs on uniform machines

Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series

Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA

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