TY - JOUR
KW - Supply chain management
KW - Collaborative planning
KW - Genetic algorithm
KW - Scheduling
AU - Guido Berning
AU - Marcus Brandenburg
AU - Korhan Gürsoy
AU - Jürgen Kussi
AU - Vipul Mehta
AU - Franz-Josef Tölle
AB - We consider a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm (GA) based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries.
BT - Computers & Chemical Engineering
DO - 10.1016/j.compchemeng.2003.09.004
M1 - 6
N1 - FOCAPO 2003 Special issue
N2 - We consider a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm (GA) based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries.
PY - 2004
SP - 913
EP - 927
T2 - Computers & Chemical Engineering
TI - Integrating collaborative planning and supply chain optimization for the chemical process industry (I)—methodology
UR - https://www.sciencedirect.com/science/article/pii/S0098135403002321
VL - 28
SN - 0098-1354
ER -