Abstract
With the rapid growth of electricity demand, many governments around the world have implemented the energy-conscious policy such as time-of-use policy. This paper addresses a bi-objective single machine scheduling with the total tardiness and electricity cost minimization under time-of-use tariffs. The problem is formulated as a mixed integer programming model. The CPLEX solver solves a small size instance to validate the model. We also describe the procedure to obtain the set of non-dominated solution using commercial solver. The complexity of the model is tested on several problem instances. The results show that the problem is hard to solve even for medium size instances. Hence, we propose a genetic algorithm with random insertion to obtain the set of Pareto solutions for large instances.
| Original language | English |
|---|---|
| Title of host publication | 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018 |
| Publisher | IEEE Computer Society |
| Pages | 137-141 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781538667866 |
| DOIs | |
| Publication status | Published - 2019 Jan 9 |
| Event | 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018 - Bangkok, Thailand Duration: 2018 Dec 16 → 2018 Dec 19 |
Publication series
| Name | IEEE International Conference on Industrial Engineering and Engineering Management |
|---|---|
| Volume | 2019-December |
| ISSN (Print) | 2157-3611 |
| ISSN (Electronic) | 2157-362X |
Conference
| Conference | 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018 |
|---|---|
| Country | Thailand |
| City | Bangkok |
| Period | 18/12/16 → 18/12/19 |
Fingerprint
Keywords
- Bi-objective
- electricity cost
- single machine
- time-of-use
- total weighted tardiness
ASJC Scopus subject areas
- Business, Management and Accounting (miscellaneous)
- Industrial and Manufacturing Engineering
- Safety, Risk, Reliability and Quality
Cite this
A Mix Integer Programming Model for Bi-objective Single Machine with Total Weighted Tardiness and Electricity Cost under Time-of-use Tariffs. / Kurniawan, B.; Gozali, A. A.; Weng, W.; Fujimura, Shigeru.
2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018. IEEE Computer Society, 2019. p. 137-141 8607420 (IEEE International Conference on Industrial Engineering and Engineering Management; Vol. 2019-December).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A Mix Integer Programming Model for Bi-objective Single Machine with Total Weighted Tardiness and Electricity Cost under Time-of-use Tariffs
AU - Kurniawan, B.
AU - Gozali, A. A.
AU - Weng, W.
AU - Fujimura, Shigeru
PY - 2019/1/9
Y1 - 2019/1/9
N2 - With the rapid growth of electricity demand, many governments around the world have implemented the energy-conscious policy such as time-of-use policy. This paper addresses a bi-objective single machine scheduling with the total tardiness and electricity cost minimization under time-of-use tariffs. The problem is formulated as a mixed integer programming model. The CPLEX solver solves a small size instance to validate the model. We also describe the procedure to obtain the set of non-dominated solution using commercial solver. The complexity of the model is tested on several problem instances. The results show that the problem is hard to solve even for medium size instances. Hence, we propose a genetic algorithm with random insertion to obtain the set of Pareto solutions for large instances.
AB - With the rapid growth of electricity demand, many governments around the world have implemented the energy-conscious policy such as time-of-use policy. This paper addresses a bi-objective single machine scheduling with the total tardiness and electricity cost minimization under time-of-use tariffs. The problem is formulated as a mixed integer programming model. The CPLEX solver solves a small size instance to validate the model. We also describe the procedure to obtain the set of non-dominated solution using commercial solver. The complexity of the model is tested on several problem instances. The results show that the problem is hard to solve even for medium size instances. Hence, we propose a genetic algorithm with random insertion to obtain the set of Pareto solutions for large instances.
KW - Bi-objective
KW - electricity cost
KW - single machine
KW - time-of-use
KW - total weighted tardiness
UR - http://www.scopus.com/inward/record.url?scp=85061791752&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061791752&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2018.8607420
DO - 10.1109/IEEM.2018.8607420
M3 - Conference contribution
AN - SCOPUS:85061791752
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 137
EP - 141
BT - 2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018
PB - IEEE Computer Society
ER -