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Optimizing the Bonus-Penalty Structure of Large- Scale Project Scheduling Problem: A Flexible Resource-Constrained View

机译:优化大型项目调度问题的奖惩结构:一种灵活的资源受限视图

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In this paper, we optimize the bonus-penalty structure of large-scale project on flexible resource-constraint with a Stackelberg model, and propose a parameter of Optimization-Level to analyze the impact about the Hire-Index influences on the degree of the optimization We find that the optimization of Incentive-Intensity can make the bonus-penalty structure more effective, and the client will gain their maximal benefits. However, the project scheduling and the bonus-penalty structure can be optimized better, because of the flexible resource. The Hire-Index of the resource influences the degree of the optimization very much, and the lower the better, whereas the worse.
机译:本文利用Stackelberg模型在柔性资源约束下优化大型项目的罚金结构,并提出了优化级别的参数,以分析雇佣指数对优化程度的影响我们发现,激励强度的优化可以使奖金-罚金结构更有效,并且客户将获得最大的收益。但是,由于资源的灵活性,可以更好地优化项目进度和奖罚结构。资源的雇佣指数对优化程度有很大的影响,数值越低越好,反之则越差。

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