TY - JOUR
T1 - Production Planning, Scheduling, and Process Control System in Microalgae and Biogas Supply Chain
AU - Nugroho, Yohanes Kristianto
AU - Zhu, Liandong
PY - 2019/2/6
Y1 - 2019/2/6
N2 - Biomass feedstock is a potential solution to the future source of biofuels and fine chemicals. A major challenge of its availability to meet energy demands extends the scope of production planning from single- to multilocations. However, multilocation production planning needs an integrated production scheduling to minimize idle times and overstocks and process control to hedge against any change in production planning. This article models an integration of production planning, scheduling and process control system, and formulates the model as a bilevel generalized disjunctive programming (GDP). We use a reformulation technique that converts bilevel into a single-level programming. We solve the model by using Branch and Reduce method and add outer approximation (OA) cutting plane at each lower bounding iteration. The computational result shows that the supply chain can mitigate stock out or over stock and generate no delivery delay. In terms of computational results, we find that the algorithm is capable of minimizing optimality gaps within the range of allowable error.
AB - Biomass feedstock is a potential solution to the future source of biofuels and fine chemicals. A major challenge of its availability to meet energy demands extends the scope of production planning from single- to multilocations. However, multilocation production planning needs an integrated production scheduling to minimize idle times and overstocks and process control to hedge against any change in production planning. This article models an integration of production planning, scheduling and process control system, and formulates the model as a bilevel generalized disjunctive programming (GDP). We use a reformulation technique that converts bilevel into a single-level programming. We solve the model by using Branch and Reduce method and add outer approximation (OA) cutting plane at each lower bounding iteration. The computational result shows that the supply chain can mitigate stock out or over stock and generate no delivery delay. In terms of computational results, we find that the algorithm is capable of minimizing optimality gaps within the range of allowable error.
UR - http://www.scopus.com/inward/record.url?scp=85060517533&partnerID=8YFLogxK
U2 - 10.1021/acs.iecr.8b03960
DO - 10.1021/acs.iecr.8b03960
M3 - Journal article
SN - 0888-5885
VL - 58
SP - 1941
EP - 1956
JO - Industrial & Engineering Chemistry Research
JF - Industrial & Engineering Chemistry Research
IS - 5
ER -