Treffer: MINIMIZING PERSONNEL COSTS USING LINEAR PROGRAMMING TOOLS ON THE EXAMPLE OF A SERVICE BUSINESS.

Purpose: The aim of this article is to apply theories concerning the optimization of employment levels using linear programming methods based on the assignment problem. Design/methodology/approach: The research was based on a review of literature on business management and the problem of assignment. In the author's opinion, studies showing the practical possibilities of this type of algorithm fill a cognitive and application gap in the field of management sciences. The research part of the thesis formulates a linear programming model for service activities, concerning the assignment of employees to projects, taking into account their specializations. Findings: The article expresses the view that the optimal allocation of labor resources has a beneficial impact not only on employment costs but also on strengthening the flexibility of enterprises. Currently, companies must strive for a well-thought-out and rapid allocation of their resources in order to be able to effectively take advantage of market opportunities. The assignment problem can partially support these processes. The article develops a linear programming model for the allocation of employees to projects, taking into account their specializations. As a result, a combination of allocations was found that generates the lowest employment costs, taking into account other constraints, i.e., employee working time and task duration, employee availability, and required completion dates. Research limitations/implications: Developing optimization models requires understanding and formulating mathematical functions. For many decision-makers, this is a demotivating factor in exploring the implementation of processes with the support of available programming tools. Practical implications: The model can be adapted to the conditions of the decision-making task. It can serve as a starting point for various forms of activity in which the individual characteristics of objects and their preferences for the tasks to be performed are known. Originality/value: It should be emphasized that this article can be a valuable source of knowledge on optimal resource allocation. The proposed algorithm in its presented form can be used in many areas of management. It can also be modified depending on changing input parameters. [ABSTRACT FROM AUTHOR]

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