.png){kind=icon}
返回
Parallel integer optimization for crew scheduling
.png){kind=icon}
PRE
AI
DOI：10.1023/A:1019293017474.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Performance aspects of a Lagrangian relaxation based heuristic for solving large 0-1 integer linear programs are discussed. In particular, we look at its application to airline and; railway crew scheduling problems. We present a scalable parallelization of the original algorithm used in production at Carmen Systems AB, Goteborg, Sweden, based on distributing the variables. A lazy variant of this approach which decouples communication and computation is even useful on networks of workstations. Furthermore, we develop a new sequential active set strategy which requires less work and is better adapted to the memory hierarchy properties of modern RISC processors. This algorithm is also suited for parallelization on a moderate number of networked workstations.
Keyword:
airline crew scheduling
combinatorial optimization
Lagrangian relaxation
memory hierarchy
parallel 0/1 integer linear programming
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
