Abstract
Scrum is an agile software development framework followed nowadays by many software companies worldwide. Since it is an iterative and incremental methodology, the software is developed in releases. For each release, the software development team and the customer agree upon a development plan. However, the context of the software project may change due to unpredicted circumstances that generally arise, for example, new software requirements or changes in the development team. Consequently, these factors force the release plan to be adjusted. When the release plan is modified, it is necessary to consider at least four criteria to minimize the economic and operational impact of these changes. Therefore, this activity can be analyzed as a multi-objective problem. In the last three decades, multi-objective evolutionary algorithms have become an effective and efficient tool to solve multi-objective problems. In this paper, we evaluate three multi-objective optimization approaches when solving the release plan rescheduling problem. Mainly, we focus our investigation on analyzing the conflict between the considered objectives and on the performance of the Pareto-based, the indicator-based, and the decomposition-based multi-objective optimization approaches.
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García-Nájera, A., Zapotecas-Martínez, S., Falcón-Cardona, J.G., Cervantes, H. (2021). Multi-objective Release Plan Rescheduling in Agile Software Development. In: Batyrshin, I., Gelbukh, A., Sidorov, G. (eds) Advances in Computational Intelligence. MICAI 2021. Lecture Notes in Computer Science(), vol 13067. Springer, Cham. https://doi.org/10.1007/978-3-030-89817-5_30
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