TY - JOUR
T1 - Efficient approximation scheme for job assignment in a multi-factory environment
AU - Wachtel, Guy
AU - Elalouf, Amir
N1 - Publisher Copyright:
© 2020 Taylor & Francis Group, LLC.
PY - 2020/10/2
Y1 - 2020/10/2
N2 - As manufacturing environments are getting increasingly decentralized, while the customer diversity of requirements is continuously growing, it becomes important for manufacturers to optimize complex production processes across multiple factories. We propose a dynamic algorithm based on a fully polynomial approximation scheme (FPTAS) to schedule jobs between a main factory and another set of sub-factories. The decision maker will balance workload across the two sets of factories, while considering each job’s specific properties such as complexity, due-date, profit earned if completed on time. We validated the algorithm applicability in real life, using data provided by a company that is involved in building development. Our results suggest that our algorithm has the potential to assist decision makers in efficiently assigning jobs across multiple processors. To the best of our knowledge, the current paper is the first to propose and design a rapid and efficient FPTAS approximation for a multi-factory setting.
AB - As manufacturing environments are getting increasingly decentralized, while the customer diversity of requirements is continuously growing, it becomes important for manufacturers to optimize complex production processes across multiple factories. We propose a dynamic algorithm based on a fully polynomial approximation scheme (FPTAS) to schedule jobs between a main factory and another set of sub-factories. The decision maker will balance workload across the two sets of factories, while considering each job’s specific properties such as complexity, due-date, profit earned if completed on time. We validated the algorithm applicability in real life, using data provided by a company that is involved in building development. Our results suggest that our algorithm has the potential to assist decision makers in efficiently assigning jobs across multiple processors. To the best of our knowledge, the current paper is the first to propose and design a rapid and efficient FPTAS approximation for a multi-factory setting.
KW - Decision making
KW - FPTAS
KW - Multi-factory
KW - scheduling
UR - http://www.scopus.com/inward/record.url?scp=85089173521&partnerID=8YFLogxK
U2 - 10.1080/21681015.2020.1801867
DO - 10.1080/21681015.2020.1801867
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AN - SCOPUS:85089173521
SN - 2168-1015
VL - 37
SP - 313
EP - 320
JO - Journal of Industrial and Production Engineering
JF - Journal of Industrial and Production Engineering
IS - 7
ER -