Formulations, Features of Solution Space, and Algorithms for Line-Pure Seru System Conversion

The line-seru conversion is usually used to improve productivity, especially in volatile business environment. Due to the simplicity, most researches focused on line-pure seru system conversion. We summarize the two existing models (i.e., a biobjective model and a single-objective model) of line-pure system conversion and formulate the three other usually used single-objective models in an integrated framework by combining evaluated performances and constraints. Subsequently, we analyze the solution space features of line-pure seru system conversion by dividing the whole solution space into several subspaces according to the number of serus. We focus on investigating the features between C-max (and TLH) and subspaces. Thirdly, according to the distinct features between C-max (and TLH) and subspaces, we propose four effective algorithms to solve the four single-objective models, respectively. Finally, we evaluate the computational performance of the developed algorithms by comparing with enumeration based on extensive experiments.