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首页> 外文会议>Portland International Conference on Management of Engineering and Technology >Optimizing Resource Allocation in a Portfolio of Projects Related to Technology Infusion Using Heuristic and Meta-Heuristic Methods
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Optimizing Resource Allocation in a Portfolio of Projects Related to Technology Infusion Using Heuristic and Meta-Heuristic Methods

机译：使用启发式和元启发式方法优化与技术注入相关的项目组合中的资源分配

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摘要

This paper proposes a method to address the planning and scheduling required to infuse technologies into a portfolio of product development projects. Definitive selection of technologies for infusion cannot be applied without taking into account available resources, time required to mature technologies and the interactions among them. Portfolio selection and the scheduling process have often been treated separately although they are interdependent. This research aims to bridge the gap between portfolio scheduling and technology infusion by considering both with realistic performance dynamics, in which the iterative nature of activities is included in the model. Given these improvements, methods for effectively allocating resources in a portfolio of projects related to technology infusion are recommended. Initially, a heuristic method is proposed based on priority rules. However, as the assumptions of the model are loosened a novel method is suggested that combines Genetic Algorithm (GA) and Artificial Bee Colony (ABC) approaches. Numerical results indicate that the hybrid meta-heuristic method based on GA-ABC is effective in finding good resource allocations while considering rework. At the same time, results confirm that rework can dramatically affect the projects that comprise the portfolio and therefore rework should be included in these analyses.
机译：本文提出了一种解决方案，以解决将技术注入产品开发项目组合所需的计划和日程安排。在不考虑可用资源，成熟技术所需的时间以及它们之间的相互作用的情况下，不能对输注技术进行明确的选择。尽管项目组合选择和计划过程是相互依赖的，但它们经常被分开处理。这项研究旨在通过考虑现实的绩效动力学来弥补投资组合计划与技术注入之间的差距，在模型中包括了活动的迭代性质。考虑到这些改进，推荐了在与技术注入相关的项目组合中有效分配资源的方法。最初，提出了一种基于优先级规则的启发式方法。但是，随着模型假设的放松，提出了一种结合遗传算法（GA）和人工蜂群（ABC）方法的新方法。数值结果表明，基于GA-ABC的混合元启发式方法在考虑返工的情况下可以有效地找到良好的资源分配。同时，结果证实返工会极大地影响组成投资组合的项目，因此返工应包括在这些分析中。

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