TY - GEN
T1 - Electricity power cost-aware scheduling of jobs on parallel batch processing machines
AU - Rocholl, Jens
AU - Mönch, Lars
AU - Fowler, John W.
N1 - Funding Information:
The research of the first and second author is funded in parts by a research grant from the University of Hagen within the MaXFab project. The authors gratefully acknowledge this financial support. Parts of this research were carried out whilst the third author was visiting the Chair of Enterprise-wide Software Systems at University of Hagen.
Publisher Copyright:
© 2018 IEEE
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/1/31
Y1 - 2019/1/31
N2 - We discuss a bicriteria scheduling problem for parallel identical batch processing machines in semiconductor wafer fabrication facilities (wafer fabs). Only jobs that belong to the same family can be batched together. The performance measures of interest are the total weighted completion time and the electricity power cost. Unequal release dates of the jobs are taken into account. The jobs can have nonidentical sizes. We provide a Mixed Integer Linear Programming (MILP) formulation for the general setting. Moreover, we analyze the special case where all jobs have the same size, the maximum batch size is an integer multiple of this job size, and all jobs are available at time zero. We prove certain properties of Pareto-optimal schedules for this special case. These properties lead to a MILP formulation that is more tractable than the one for the general setting. We perform computational experiments with the ε-constraint method for both formulations.
AB - We discuss a bicriteria scheduling problem for parallel identical batch processing machines in semiconductor wafer fabrication facilities (wafer fabs). Only jobs that belong to the same family can be batched together. The performance measures of interest are the total weighted completion time and the electricity power cost. Unequal release dates of the jobs are taken into account. The jobs can have nonidentical sizes. We provide a Mixed Integer Linear Programming (MILP) formulation for the general setting. Moreover, we analyze the special case where all jobs have the same size, the maximum batch size is an integer multiple of this job size, and all jobs are available at time zero. We prove certain properties of Pareto-optimal schedules for this special case. These properties lead to a MILP formulation that is more tractable than the one for the general setting. We perform computational experiments with the ε-constraint method for both formulations.
UR - http://www.scopus.com/inward/record.url?scp=85062596989&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062596989&partnerID=8YFLogxK
U2 - 10.1109/WSC.2018.8632342
DO - 10.1109/WSC.2018.8632342
M3 - Conference contribution
AN - SCOPUS:85062596989
T3 - Proceedings - Winter Simulation Conference
SP - 3420
EP - 3431
BT - WSC 2018 - 2018 Winter Simulation Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Winter Simulation Conference, WSC 2018
Y2 - 9 December 2018 through 12 December 2018
ER -