牛顿式算法用于反向优化:加权瓶,哈明距离和l∞ - 规范目标
Kristóf Bérczi1, Lydia Mirabel Mendoza-Cadena1, Kitti Varga1
1MTA-ELTE Matroid Optimization Research Group, and HUN-REN-ELTE Egerváry Research Group, and Department of Operations Research, Eötvös Loránd University, Budapest, Hungary.
概括
本研究通过修改成本来解决逆优化问题,使给定的解决方案成为最佳. 它介绍了加权瓶Hamming距离和加权L-无限度规范目标的高效算法.
科学领域:
- 优化理论 优化理论
- 组合优化的优化.
- 算法设计 算法设计
背景情况:
- 反向优化问题涉及调整参数,使给定的解决方案成为最佳的.
- 这项研究的重点是使用线性成本函数设置最低成本.
- 该研究考虑在特定范围内使用偏差向量来修改成本.
研究的目的:
- 在两个具体目标下开发逆优化问题的算法:加权瓶哈明距离和加权L-无限度规范.
- 分析为这些目标找到最佳偏差向量的计算复杂性.
- 为了探索偏差向量具有边界坐标的一般模型.
主要方法:
- 对于加权瓶的哈明距离: 呈现了一个纯粹的组合算法.
- 对于加权的L-无限度规范:导出了最小-最大的表征,并为单位权重提供了伪多项式算法.
- 这两种方法都假定有一个算法可以解决底层的组合优化问题.
主要成果:
- 一个强大的多项式时间算法,用于加权瓶汉明距离目标.
- 一个伪多项式时间算法,用于加权的L-无限度规范目标,它对于单位重量是强有力的多项式.
- 这些算法是为具有边界偏差向量坐标的一般模型而设计的.
结论:
- 提供了高效的算法,以解决与特定距离指标的逆最小成本优化问题.
- 这项研究有助于理解反向优化中的计算复杂性.
- 这些发现提供了实用方法来调整问题参数,以实现所需的最佳解决方案.
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