多指标排序是排序领域的重要研究方向，其问题形式包括以下四种：(1) 分层优化；(2) 约束优化；(3) 正组合优化；(4) Pareto 优化。这四种形式的多指标排序广泛应用于生产与管理之中。本项目的研究内容包括：(1) 多指标排序(特别是多代理排序)中的历史遗留问题；(2) 可自由下线的平行批机器上的多指标排序；(3) 柔性原始工件整体错位下的重新排序等。这些问题也将与各种新兴排序模型结合起来形成广泛的研究内涵。本项目的目标是在全新的理论工具的基础上对需要研究的多指标排序问题进行计算复杂性分析、寻求有效的多项式时间算法、设计性能良好的近似算法。在成果表现方面，我们将解决多指标排序中若干历史遗留问题，并在可及时下线的平行批机器排序和柔性原始工件整体错位下的重新排序模型下对多指标排序给出完整的研究结果。

Scheduling with multiple criteria (multi-criteria scheduling) is an important research direction in scheduling theory, which includes the following four forms of problems: (1) Hierarchical Optimization; (2) Constrained Optimization; (3) Positive Combination Optimization; (4) Pareto Optimization. These forms of scheduling have been widely applied in productions and managements. The research of this project includes the following aspects: (1) Open problems in multi-criteria scheduling (especially in multi-agent scheduling); (2) Multi-criteria scheduling on drop-line parallel-batch machines; (3) Rescheduling with flexible original jobs under global disruption and so on. These problems are also combined with various new scheduling models to form a broad research perceptions. Based on totally new theoretical tools, the goal of this project is to present complexity analysis, find efficient polynomial-time algorithms and design polynomial-time approximation algorithms with good performances. In the aspect of expression of achievements， we will solve several open problems in multi-criteria scheduling, and provide complete research results for multi-criteria scheduling on drop-line parallel-batch machines and rescheduling with flexible original jobs under global disruption.