Abstract
Workers’ absences are a common disruption to the provision of tasks. They make it necessary to modify task assignment, which amounts to finding suitable substitutions. Sometimes it happens that the competences of the available workers, with given constraints, e.g. hour limits, are not sufficient to find an admissible assignment modification. Therefore, it is desirable to develop a so-called robust personnel competence structure. In the case of workers’ absences, a robust competence structure is a structure that allows one to find a modification of the assignment under every possible scenario of disruption. In other words, the following question is considered: does there exist, and if so, what is the competence structure robust to the disruption caused by an unexpected personnel absence? The number of potential solution variants is related to the number of competences that can be improved. For each variant, there could exist many cases of worker absence (absence of one worker, two workers, etc.). Moreover, for these, there could also exist many assignment modification variants. This an NP-hard problem. In the context of the scale of problems encountered in practice, searching for solutions using well-known algorithms (based on an exhaustive search) is a time-consuming process which does not guarantee that an admissible solution will be found. In the present study, a sufficient conditions are proposed, the fulfilment of which guarantees the existence of a non-empty set of admissible solutions. Declarative modelling and computer implementation in the form of constraint logic programming (CLP) have been applied. The potential of the proposed solution is illustrated with examples.
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Szwarc, E., Bocewicz, G., Bach-Dąbrowska, I., Banaszak, Z. (2019). Declarative Model of Competences Assessment Robust to Personnel Absence. In: Damaševičius, R., Vasiljevienė, G. (eds) Information and Software Technologies. ICIST 2019. Communications in Computer and Information Science, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-030-30275-7_2
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