Polytechnic and design, Vol. 10 No. 4, 2022.
Professional paper
https://doi.org/10.19279/TVZ.PD.2022-10-4-05
GENERATING AND OPTIMIZING SCHEDULES USING GENETIC ALGORITHM
Toni Bedalov
; Zagreb University of Applied Sciences, Vrbik 8, 10000 Zagreb, Croatia, student
Željko Kovačević
; Zagreb University of Applied Sciences, Vrbik 8, 10000 Zagreb, Croatia, student
Abstract
This paper describes the process of generating and optimizing company employee schedules using genetic algorithm. In general, evolutionary computing has long been used to solve these types of problems where it is necessary to search large areas of all possible solutions in the shortest possible time. Since such optimization problems are most often of "NP-hard" complexity, the "brute force" approach is not applicable because it usually costs too much CPU time. In solving our problem, we used all genetic operators (selection, crossover, and mutation), while for the needs of implementation, an application in the Java programming language was developed. The obtained results in almost all cases represent optimal solutions (schedules), and when it is not possible to reach the optimal solution, our approach gives one or more solutions that are closest to the required optimum. The individual genetic operators and the obtained results are described below.
Keywords
genetic algorithms; evolutionary computing; optimization; schedule
Hrčak ID:
294328
URI
Publication date:
16.1.2023.
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