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A multi-objective model for multi-project scheduling and multi-skilled staff assignment for IT product development considering competency evolution

机译:考虑能力发展的用于IT产品开发的多项目计划和多技能员工分配的多目标模型

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We address a multi-skill project scheduling problem for IT product development in this article. The goal is for product development managers to be able to generate an initial schedule at an early stage of development activities. Due to the complexity of the product structure and functionality, an IT product development effort is divided into multiple projects. Each project includes several tasks, and each task must be completed by an employee who has mastered a certain skill to complete it. A pool of multi-skilled employees is available, and the employees' skill efficiencies are influenced by both learning and forgetting phenomena. Based on the real-world demands of product development managers, three objectives are simultaneously considered: skill efficiency gain, product development cycle time and costs. To solve this problem, we propose a multi-objective non-linear mixed integer programming model. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is designed to generate an approximation to the optimal Pareto front of this NP-hard multi-objective optimisation problem. The algorithm produces feasible schedules for all the development projects using the serial schedule generation scheme. We adopt penalty values and individual employee adjustments to address resource conflicts and constraint violations. A weighted ideal point method is used to select the final solution from the approximate Pareto solution set. An application case of a new electrical energy saving product implementation in a leading electrical device company in China is used to illustrate the proposed model and algorithm.
机译:在本文中,我们解决了针对IT产品开发的多技能项目计划问题。产品开发经理的目标是能够在开发活动的早期阶段制定初始计划。由于产品结构和功能的复杂性,IT产品开发工作分为多个项目。每个项目都包含多个任务,并且每个任务必须由已掌握某种技能的员工来完成。拥有一批多技能的员工,并且员工的技能效率受学习和遗忘现象的影响。基于产品开发经理的实际需求,同时考虑了三个目标:技能效率增益,产品开发周期时间和成本。为了解决这个问题,我们提出了一个多目标非线性混合整数规划模型。非支配排序遗传算法II(NSGA-II)旨在生成此NP-hard多目标优化问题的最优Pareto前沿的近似值。该算法使用串行进度表生成方案为所有开发项目生成可行的进度表。我们采用惩罚值和员工个人调整来解决资源冲突和约束冲突。加权理想点法用于从近似Pareto解集中选择最终解。以中国某著名电器公司的一种新型节能产品的应用案例为例,说明了所提出的模型和算法。

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