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A Multi-objective Genetic Algorithm for Software Development Team Staffing Based on Personality Types

机译:基于人格类型的软件开发团队人员配置多目标遗传算法

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This paper proposes a multi-objective genetic algorithm for software project team staffing that focuses on optimizing human resource usage based on technical skills and personality traits of software developers. Human factors are recognized as critical aspects affecting the rate of success of software projects, as well as other properties, such as productivity, software quality, performance, and job satisfaction. However, managers often rely solely on technical criteria to staff their projects, which risks overlooking these important aspects of software development, such as the abilities and work styles of developers. The behaviour and scalability of the algorithm was validated against a series of hypothetical projects of varying size and complexity, and also through a real-world project of an SME in the local IT industry. The approach demonstrated a sufficient ability to generate both feasible and optimal staffing solutions by assigning developers most technically competent and suited personality-wise for each project task.
机译:本文提出了一种多目标遗传算法,适用于软件项目团队人员配置,专注于根据技术技能和软件开发人员的人格特征优化人力资源使用。人为因素被认为是影响软件项目成功率的关键方面,以及其他属性,如生产力,软件质量,性能和工作满意度。然而,管理人员经常完全依赖于工作人员的技术标准,这忽视了软件开发的这些重要方面,例如开发人员的能力和工作风格。算法的行为和可扩展性与一系列不同尺寸和复杂性的假设项目验证,以及当地IT行业中小企业的真实世界项目。该方法证明了通过在每个项目任务中分配最佳技术表现和适合个性的开发人员来说,通过为每个项目任务分配最佳的人格而产生可行和最佳的人员配置解决方案的足够能力。

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