In this paper, we present a novel scheduling problem, the stem cell culturing problem (SCP), which is identified in an attempt to improve the productivity of a manufacturing system producing a commercialized autologous stem cell therapeutic product for treating an incurable disease. For a given therapeutic product along with the corresponding manufacturing process, which is called the stem cell culture process, SCP is the problem of maximizing the number of produced units of a therapeutic product during a given horizon while satisfying the operational constraints stem from unique characteristics of the stem cell culture process and the related resources. After we formally define SCP, we show that SCP is NP-hard in the strong sense. Then, we present an integer optimization model based on the concept of a daily mode. The computational performance of the proposed model is analyzed with a general purpose integer optimization software. Moreover, based on this model, we propose an ecient LP-based heuristic algorithm which yields provably good solutions within a short time. Through computational experiments, we demonstrate that the proposed algorithm is both effective and efficient in solving practically-sized instances.
sysopt-202101, Seoul National University, 1Gwanak-ro Gwanak-gu Seoul 08826 Korea, August/2021