TASK SELECTION AND ALLOCATION METHOD BASED ON SCRUM METODOLOGY USING POPULATION ALGORITHMS

Author(s): Troshkin N.R., Vishnevskaya T.I.

Rubric: Information technology

DOI: 10.21777/2500-2112-2025-3-83-95

Release: 2025-3 (52)

Pages: 83-95

Keywords: task allocation, genetic algorithm, bacterial chemotaxis algorithm, population algorithms, knapsack problem, combinatorial optimization, project management, Scrum methodology

Annotation: The article describes the problem of task selection and distribution among executors in the context of software pro- jects using Scrum methodology. The solution to this problem is proposed by reducing it to the problem of multiple knapsacks and solving it using population algorithms, in particular, the ensemble of genetic algorithm and bacte- rial chemotaxis algorithm. The article presents a model for calculating the priority of a task and its execution time for a particular performer. Classes of input data are described. The main stages of the algorithms and the values of their tuning parameters are explained. A metric for evaluating the quality of the results of the proposed method has been developed. The set of algorithms parameters, at which the quality index will be high for most classes of input data, is defined. The comparison of the operating time of the software implementation of the algorithms and their combinations, as well as the quality of the obtained calculation results, is given. Conclusions are drawn about the applicability of the ensemble algorithms to the selected classes of input data. The results of the study show the effectiveness of using the developed method for distributing work in comparison with its individual algorithms.

Bibliography: Troshkin N.R., Vishnevskaya T.I. TASK SELECTION AND ALLOCATION METHOD BASED ON SCRUM METODOLOGY USING POPULATION ALGORITHMS // Education Resources and Technologies. – 2025. – № 3 (52). – С. 83-95. doi: 10.21777/2500-2112-2025-3-83-95