Abstract
Digitization and automation highly increases the amount of available process data in logistics. To use data in a way that employees rights and values are adequatly considered, the HPAO (human preference-aware optimization) research project is investigating new possibilities of data usage in personnel deployment planning. Technical and ethical aspects are investigated equally. Artificial Intelligence Algorithms can take large amounts of data and contraints in the allocation in account and are thus considered to match workers to workplaces in the project. An operational system will be created by developing a survey-based methodology to measure staff preferences, identifying suitable allocation algorithms and producing mock-ups of the software, which will be examined in user studies for applicability and transparency. This serves as a case study and basis for the development of ethical guidelines for employee-centered technology.
Translated title of the contribution | Human Preference-aware Staff Scheduling with Artificial Intelligence in Logistics |
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Original language | German |
Pages (from-to) | 908-912 |
Number of pages | 5 |
Journal | ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb |
Volume | 116 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2021 |