Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/258115 
Year of Publication: 
2021
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 9 [Issue:] 1 [Article No.:] 25 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-17
Publisher: 
MDPI, Basel
Abstract: 
The assignment problem (AP) is a discrete and combinatorial problem where agents are assigned to perform tasks for efficiency maximization or cost (time) minimization. AP is a part of human resource project management (HRPM). The AP optimization model, with deterministic parameters describing agent-task performance, can be easily solved, but it is characteristic of standard, well-known projects realized in a quiet environment. When considering new (innovation or innovative) projects or projects performed in very turbulent times, the parameter estimation becomes more complex (in extreme cases, even the use of the probability calculus is not recommended). Therefore, we suggest an algorithm combining binary programming with scenario planning and applying the optimism coefficient, which describes the manager's nature (attitude towards risk). The procedure is designed for one-shot decisions (i.e., for situations where the selected alternative is performed only once) and pure strategies (the execution of a weighted combination of several decision variants is not possible).
Subjects: 
assignment problem
human resource project management
innovative and innovation projects
mathematical model and optimization
turbulent times
uncertainty and risk
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Creative Commons License: 
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Document Type: 
Article
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