Reuse oriented group maintenance scheduling based on Hybrid Genetic Algorithm and Tabu Search

Reuse of facilities can bring manufacturers not only less investment but also green images, whereas it requires much maintenance to guarantee the reusability of facilities, which could lead to higher maintenance cost and more production lost. In this paper, a preventive maintenance scheduling method for complex series-parallel system is proposed under group maintenance policy utilizing intelligent algorithms. Hybrid Genetic Algorithm (HGA) and Tabu Search (TS) are employed and compared in terms of time complexity and effectiveness. A case study is then presented. It is verified that group maintenance policy can enhance the reuse of facilities as well as reduce maintenance cost and production lost in the long run. In addition, it can be concluded that HGA is more effective but more time consuming compared with TS.