NSGA-II for Parallel Machine Scheduling with Tardiness and Extra QoS Cost Considerations

We investigate parallel machine scheduling problem of matching the orders and factories with the multiobjective of minimizing the total tardiness and the extra quality of service (QoS) cost in this work. We establish a multi-objective integer programming (MOIP) model, and devise an epsilon constrain...

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Vydané v:	Proceedings of ICSSSM (Print) s. 1 - 7
Hlavní autori:	Zheng, Feifeng, Jin, Kaiyuan
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.07.2019
Predmet:	Epsilon constraint algorithm Genetic algorithms Mathematical model Non-dominated sorting genetic algorithm II (NSGA-II) Parallel machine Parallel machines Production facilities Quality of service Quality of service (QoS) Scheduling
ISSN:	2161-1904
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Popis
Shrnutí:	We investigate parallel machine scheduling problem of matching the orders and factories with the multiobjective of minimizing the total tardiness and the extra quality of service (QoS) cost in this work. We establish a multi-objective integer programming (MOIP) model, and devise an epsilon constraint ( ε-constraint) algorithm together with Non-dominated Sorting Genetic Algorithm II (NSGA-II). The ε-constraint method produces exact solutions for small order instances, while the NSGA-II can efficiently solve large-scale instances. Numerical experiments validate the proposed model and algorithms.
ISSN:	2161-1904
DOI:	10.1109/ICSSSM.2019.8887842