%A Chen SONG, Xiaohong GUAN, Qianchuan ZHAO, Qing-Shan JIA %T Remanufacturing planning based on constrained ordinal optimization %0 Journal Article %D 2011 %J Front. Electr. Electron. Eng. %J Frontiers of Electrical and Electronic Engineering %@ 2095-2732 %R 10.1007/s11460-011-0162-y %P 443-452 %V 6 %N 3 %U {https://journal.hep.com.cn/fee/EN/10.1007/s11460-011-0162-y %8 2011-09-05 %X

Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size, uncertainties, complicated constraints, etc. In this paper, we present a new method based on constrained ordinal optimization (COO) for remanufacturing planning. The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model (HRFM). Numerical testing shows that our method is efficient and effective for selecting good plans with high probability. It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.