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Green scheduling model of shuttle tanker fleet considering carbon tax and variable speed factor.
- Source :
-
Journal of Cleaner Production . Oct2019, Vol. 234, p1134-1143. 10p. - Publication Year :
- 2019
-
Abstract
- Green scheduling is an important means to achieve sustainable industrial development and enhance the green efficiency of enterprises. Given the characteristics of a modern crude oil supply system, the shuttle tanker fleet green scheduling problem (FGSP) is discussed considering a carbon tax and variable tanker speed factor. To minimize the green operating cost (i.e., sum of general operating cost and carbon tax) of the tanker fleet, an integer programming model for shuttle tanker fleet green scheduling (FGSM) is established. The FGSM optimizes the number and sizes of tankers, the number and positions of floating production storage and offloading units (FPSO) at which to berth and the scheduling plan (i.e., berthing order and sailing speed) of each tanker in the fleet. Based on the column generation algorithm, a shuttle tanker fleet green scheduling algorithm is designed to solve the above model accurately. The experimental results show that considering the speed factor, the green operating cost of an example fleet decreases. For different carbon tax rates, speed optimization is an effective way to reduce the green operating cost of the fleet. The above results also show that the FGSM and algorithm can effectively solve the FGSP, improve the operation level and efficiency, and reduce the green operating cost of oil companies. • A model is established to optimize fleet design and scheduling plan. • The model aims to minimize the green operating cost of the fleet. • The model considers the impact of carbon tax and vessel speed factor. • A column generation algorithm is designed to solve the model accurately. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09596526
- Volume :
- 234
- Database :
- Academic Search Index
- Journal :
- Journal of Cleaner Production
- Publication Type :
- Academic Journal
- Accession number :
- 137683157
- Full Text :
- https://doi.org/10.1016/j.jclepro.2019.06.275