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Analysis of the multi-objective release plan rescheduling problem

delete2021-05-01
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PRE
AI
V
Víctor Escandon-Bailon
H
Humberto Cervantes
A
Abel García-Nájera *
S
Saúl Zapotecas–Martínez
DOI:10.1016/j.knosys.2021.106922delete
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Abstract

Abstract

En 中文
Software project development is a dynamic process by nature, since it is common that events such as changes in the software requirements and in the development team occur during the execution of the original project plan. When such disruptive events occur, the project plan needs to be adjusted, and the activity of adjusting the original plan in order to comply with the date and costs constraints of the project is called project rescheduling. This situation is not exclusive to whole-project plan driven approaches to software development, as it is also present when software projects are developed following agile methodologies such as Scrum. In Scrum, shorter period project plans, called release plans, are used and when disruptive events occur release plan rescheduling needs to be performed. Plan rescheduling can be modeled as a multi-objective optimization problem, however, there have been no studies that investigate the release plan rescheduling problem (RPRP) and its solution by means of multi-objective optimizers. The study presented in this paper intends to address the lack of studies of the release plan rescheduling problem and covers three fundamental topics. First, a model for the release plan rescheduling problem is proposed, which considers metrics that are particularly important to define a release plan, including story points and velocity. Second, three evolutionary multi-objective algorithms are utilized for solving a number of problem instances and an appropriate in-depth analysis of their solutions is provided. Finally, a careful examination of the solutions with respect to their practicability is performed. (c) 2021 Elsevier B.V. All rights reserved.
Keywords:
Multi-objective optimization
Release plan rescheduling problem
Scrum
Evolutionary algorithms
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Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

Organization

U
universidad autonoma metropolitana - mexico
Scholars:
5.8K
Papers: 4.4K
Citations: 4