TY - CHAP
T1 - A Biased-Randomized Discrete-Event Heuristic for the Hybrid Flow Shop Problem with Batching and Multiple Paths
AU - Laroque, Christoph
AU - Leissau, Madlene
AU - Copado, Pedro
AU - Panadero, Javier
AU - Juan, Angel A.
AU - Schumacher, Christin
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Based on a real-life use-case, this paper discusses a manufacturing scenario where different jobs be processed by a series of machines. Depending on its type, each job must follow a pre-defined route in the hybrid flow shop, where the aggregation of jobs in batches might be required at several points of a route. This process can be modeled as a hybrid flow shop problem with several additional but realistic restrictions. The objective is to find a good permutation of jobs (solution) that minimizes the makespan. Discrete-event simulation can be used to obtain the makespan value associated with any given permutation. However, to obtain high-quality solutions to the problem, simulation needs to be combined with an optimization component, e.g., a discrete-event heuristic. The proposed approach can find solutions that significantly outperform those provided by employing simulation only and can easily be extended to a simheuristic to account for random processing times.
AB - Based on a real-life use-case, this paper discusses a manufacturing scenario where different jobs be processed by a series of machines. Depending on its type, each job must follow a pre-defined route in the hybrid flow shop, where the aggregation of jobs in batches might be required at several points of a route. This process can be modeled as a hybrid flow shop problem with several additional but realistic restrictions. The objective is to find a good permutation of jobs (solution) that minimizes the makespan. Discrete-event simulation can be used to obtain the makespan value associated with any given permutation. However, to obtain high-quality solutions to the problem, simulation needs to be combined with an optimization component, e.g., a discrete-event heuristic. The proposed approach can find solutions that significantly outperform those provided by employing simulation only and can easily be extended to a simheuristic to account for random processing times.
UR - http://www.scopus.com/inward/record.url?scp=85126090187&partnerID=8YFLogxK
U2 - 10.1109/WSC52266.2021.9715442
DO - 10.1109/WSC52266.2021.9715442
M3 - Chapter
AN - SCOPUS:85126090187
T3 - Proceedings - Winter Simulation Conference
BT - 2021 Winter Simulation Conference, WSC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
ER -