Communication Papers of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS)

DOI: http://dx.doi.org/10.15439/2025F1917

Citation: Communication Papers of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 45, pages 137–143 (2025)

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Abstract. This work identifies and defines the real-world Human Resource Allocation Problem in Short-Term Employment Sector (HRAP-STE). HRAP is a subclass of the classic Human Resource Allocation Problem, adopted to the short-term employment sector, where the main everyday objective is assigning employees to the customer factories. This process has three types of actors: customers, employees, and the company from the short-term employment sector, which provides a platform for cooperation. Usually, customers require significantly more employees than their available number. Since employee assignment is usually a subject of long-term cooperation, all customers should be satisfied (at least partially) even if they do not bring the highest profit. Thus, for a company in the short-term sector, HRAP refers to three objectives: profit from projects, priority of projects, and balance in the project portfolio to satisfy all clients. In this work, we define a specific HRAP-STE problem, consider its crucial elements, and define a benchmark set of real and artificial instances. To investigate the HRAP-STE as a real case study, we apply and compare well-known (meta)heuristics (shown effective in solving real-world problems) dedicated to solving discrete problems. The computational results show the advantages of (meta)heuristics in solving instances of a larger size.

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