TY - GEN
T1 - Multi-objective optimization for periodic preventive maintenance
AU - Zade, Amir Ebrahimi
AU - Barak, Sasan
AU - Maghsoudlou, Hamidreza
AU - Toloo, Mehdi
N1 - Publisher Copyright:
© 2015 International Institute for Innovation, Industrial Engineering and Entrepreneurship - I4e2.
PY - 2016/1/12
Y1 - 2016/1/12
N2 - This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making (MCDM) technique based on the technique for order of preference by similarity to ideal solution (TOPSIS) is applied to choose the best algorithm. Comparison results confirmed supremacy of MOPSO to the other algorithms.
AB - This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making (MCDM) technique based on the technique for order of preference by similarity to ideal solution (TOPSIS) is applied to choose the best algorithm. Comparison results confirmed supremacy of MOPSO to the other algorithms.
KW - MCDM
KW - multi-objective optimization
KW - periodic maintenance
KW - scheduling
KW - single machine
KW - total earliness-tardiness
UR - http://www.scopus.com/inward/record.url?scp=84965168039&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84965168039&partnerID=8YFLogxK
U2 - 10.1109/IESM.2015.7380154
DO - 10.1109/IESM.2015.7380154
M3 - Conference contribution
AN - SCOPUS:84965168039
T3 - Proceedings of 2015 International Conference on Industrial Engineering and Systems Management, IEEE IESM 2015
SP - 173
EP - 182
BT - Proceedings of 2015 International Conference on Industrial Engineering and Systems Management, IEEE IESM 2015
A2 - Framinan, J.M.
A2 - Perez Gonzalez, P.
A2 - Artiba, A.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Conference on Industrial Engineering and Systems Management, IEEE IESM 2015
Y2 - 21 October 2015 through 23 October 2015
ER -