We tackle the problem of accelerating column generation (CG) approaches to set cover formulations in operations research. At each iteration of CG we generate a dual solution that approximately solves the LP over all columns consisting of a subset of columns in the nascent set. We refer to this linear program (LP) as the Family Restricted Master Problem (FRMP), which provides a tighter bound on the master problem at each iteration of CG, while preserving efficient inference. For example, in the single source capacitated facility location problem (SSCFLP) the family of a column $l$ associated with facility $f$ and customer set $N_l$ contains the set of columns associated with $f$ and the customer set that lies in the power set of $N_l$. The solution to FRMP optimization is attacked with a coordinate ascent method in the dual. The generation of direction of travel corresponds to solving the restricted master problem over columns corresponding to the reduced lowest cost column in each family given specific dual variables based on the incumbent dual, and is easily generated without resolving complex pricing problems. We apply our algorithm to the SSCFLP and demonstrate improved performance over two relevant baselines.
翻译:我们在业务研究中采用加速柱子生成(CG)的方法来设定配方; 在每迭代一次的CG中,我们产生一个双重解决办法,大约解决所有列的LP(LP),由一组新的列组成;我们把这一线性方案称为家庭限制总问题(FRMP),在每迭代一次的CG总问题上提供更紧密的界限,同时保持高效的推断;例如,在单一源的增强功能的设施定位问题(SSCFLLP)中,与设施有关的1列美元(ff)美元,而客户设定的$_l$($)包含与美元有关的一组列,而客户设定的1组则包含在1个电源集中的1个列。我们把FRMP优化的解决方案用一个协调点法作为双倍攻击。产生旅行方向是为了解决与每个家庭最低成本列相对应的有限总问题,因为基于现任的双重变量,而且很容易生成,而没有解决复杂的定价问题。我们将我们的算法应用于SSCFLP的2个基准,并表明业绩超过两个基准。