We consider a novel method entitled constraints reduction programming which aims to reduce the constraints in an optimization model. This method is derived from various applications of management or decision making, and has potential ability to handle a wider range of applications. Due to the high combinatorial complexity of underlying model, it is difficult to obtain a global solution. Instead, we propose three efficient greedy approaches for solving it. Preliminary experimental results show that the proposed approaches can obtain satisfactory results.
Citation
Tech Report 1703, Nanjing University of Finance & Economics, 2017
Article
View Constraints reduction programming by subset selection: a study from numerical aspect