Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Multi-objective linear programming" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
MOLPTOL – a software package for sensitivity analysis in MOLP
Autorzy:
Sitarz, Sebastian
Botor, Krzysztof
Powiązania:
https://bibliotekanauki.pl/articles/2027992.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Computer software
Multi-objective linear programming
Sensitivity analysis
Opis:
The paper introduces a new software package, MOLPTOL, for sensitivity analysis in multi-objective linear programming. In this application, which is available for free of charge on the web page (https:// sites.google.com/view/molptol), the tolerance approach as a measure of sensitivity is used. The motivation for creating MOLPTOL is the lack of such tools to date. MOLPTOL is novel for multi-criteria decision-making methods based on sensitivity analysis. The paper presents some new computational methods for obtaining the supremal tolerances as well.
Źródło:
Multiple Criteria Decision Making; 2021, 16; 140-152
2084-1531
Pojawia się w:
Multiple Criteria Decision Making
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective data envelopment analysis: A game of multiple attribute decision-making
Autorzy:
Chen, Yuh Wen
Powiązania:
https://bibliotekanauki.pl/articles/522074.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Data Envelopment Analysis (DEA)
Multi-Objective Linear Programming (MOLP)
Multiple Attribute Decision Making (MADM)
Research and Development (R&D) efficiency
Opis:
Aim/purpose ‒ The traditional data envelopment analysis (DEA) is popularly used to evaluate the relative efficiency among public or private firms by maximising each firm’s efficiency: the decision maker only considers one decision-making unit (DMU) at one time; thus, if there are n firms for computing efficiency scores, the resolution of n similar problems is necessary. Therefore, the multi-objective linear programming (MOLP) problem is used to simplify the complexity. Design/methodology/approach ‒ According to the similarity between the DEA and the multiple attribute decision making (MADM), a game of MADM is proposed to solve the DEA problem. Related definitions and proofs are provided to clarify this particular approach. Findings ‒ The multi-objective DEA is validated to be a unique MADM problem in this study: the MADM game for DEA is eventually identical to the weighting multi-objective DEA. This MADM game for DEA is used to rank ten LCD companies in Taiwan for their research and development (R&D) efficiencies to show its practical application. Research implications/limitations ‒ The main advantage of using an MADM game on the weighting multi-objective DEA is that the decision maker does not need to worry how to set these weights among DMUs/objectives, this MADM game will decide the weights among DMUs by the game theory. However, various DEA models are eventually evaluation tools. No one can guarantee us with 100% confidence that their evaluated results of DEA could be the absolute standard. Readers should analyse the results with care. Originality/value/contribution ‒ A unique link between the multi-objective CCR DEA and the MADM game for DEA is established and validated in this study. Previous scholars seldom explored and developed this breathtaking view before.
Źródło:
Journal of Economics and Management; 2019, 37; 156-177
1732-1948
Pojawia się w:
Journal of Economics and Management
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies