TY - JOUR
T1 - Optimization of bi-objective permutation flow shop scheduling with electricity cost consideration
AU - Kurniawan, B.
AU - Fujimura, S.
N1 - Funding Information:
The authors wish to thank the anonymous referees for their constructive feedback. This research is supported by the Indonesia Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan LPDP Indonesia).
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2020/12/21
Y1 - 2020/12/21
N2 - Increasing energy demand can create undesired problems for many governments worldwide. Several policies, such as time-of-use (TOU) tariffs, have been put in place to overcome such demand. The TOU policy's objective is to reduce electrical load during peak periods by shifting the use to off-peak periods. To that end, this paper addresses the bi-objective permutation flow-shop scheduling, minimizing total weighted tardiness and electricity costs. We propose a meta-heuristic algorithm based on SPEA2 to solve the problem. We conducted numerical experiments to evaluate the efficacy of the proposed algorithm by comparing it with NSGA-II. The results show that the proposed approach was more efficient compare with NSGA-II.
AB - Increasing energy demand can create undesired problems for many governments worldwide. Several policies, such as time-of-use (TOU) tariffs, have been put in place to overcome such demand. The TOU policy's objective is to reduce electrical load during peak periods by shifting the use to off-peak periods. To that end, this paper addresses the bi-objective permutation flow-shop scheduling, minimizing total weighted tardiness and electricity costs. We propose a meta-heuristic algorithm based on SPEA2 to solve the problem. We conducted numerical experiments to evaluate the efficacy of the proposed algorithm by comparing it with NSGA-II. The results show that the proposed approach was more efficient compare with NSGA-II.
UR - http://www.scopus.com/inward/record.url?scp=85098322529&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098322529&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/909/1/012045
DO - 10.1088/1757-899X/909/1/012045
M3 - Conference article
AN - SCOPUS:85098322529
SN - 1757-8981
VL - 909
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012045
T2 - 2020 International Conference on Advanced Mechanical and Industrial Engineering, ICAMIE 2020
Y2 - 8 July 2020 through 8 July 2020
ER -