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A mixed-integer linear programming model for optimal vessel scheduling in offshore oil and gas operations
1. | Curtin University, Perth, 6102, Australia |
2. | Woodside Energy Ltd, Perth, 6000, Australia |
This paper introduces a non-standard vehicle routing problem (VRP) arising in the oil and gas industry. The problem involves multiple offshore production facilities, each of which requires regular servicing by support vessels to replenish essential commodities such as food, water, fuel, and chemicals. The support vessels are also required to assist with oil off-takes, in which oil stored at a production facility is transported via hose to a waiting tanker. The problem is to schedule a series of round trips for the support vessels so that all servicing and off-take requirements are fulfilled, and total cost is minimized. Other constraints that must be considered include vessel suitability constraints (not every vessel is suitable for every facility), depot opening constraints (base servicing can only occur during specified opening periods), and off-take equipment constraints (the equipment needed for off-take support can only be deployed after certain commodities have been offloaded). Because of these additional constraints, the scheduling problem under consideration is far more difficult than the standard VRP. We formulate a mixed-integer linear programming (MILP) model for determining the optimal vessel schedule. We then verify the model theoretically and show how to compute the vessel utilization ratios for any feasible schedule. Finally, simulation results are reported for a real case study commissioned by Woodside Energy Ltd, Australia's largest dedicated oil and gas company.
References:
[1] |
AIMMS Modelling Platform, AIMMS B. V., Haarlem, Netherlands, accessed 17 April 2016, <http://www.aimms.com> Google Scholar |
[2] |
F. Alonso, M. J. Alvarez and J. E. Beasley, A tabu search algorithm for the periodic vehicle routing problem with multiple vehicle trips and accessibility restrictions, Journal of the Operational Research Society, 59 (2008), 963-976. Google Scholar |
[3] |
N. Azi, M. Gendreau and J. Y. Potvin,
An exact algorithm for a single-vehicle routing problem with time windows and multiple routes, European Journal of Operational Research, 178 (2007), 755-766.
doi: 10.1016/j.ejor.2006.02.019. |
[4] |
N. Azi, M. Gendreau and J. Y. Potvin, An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles, European Journal of Operational Research, 202 (2010), 756-763. Google Scholar |
[5] |
M. Battarra, M. Monaci and D. Vigo, An adaptive guidance approach for the heuristic solution of a minimum multiple trip vehicle routing problem, Computers and Operations Research, 36 (2009), 3041-3050. Google Scholar |
[6] |
J. Bisschop, AIMMS Optimization Modelling, Haarlem: AIMMS B. V., 2016. Google Scholar |
[7] |
J. C. S. Brandão and A. Mercer, The multi-trip vehicle routing problem, Journal of the Operational Research Society, 49 (1998), 799-805. Google Scholar |
[8] |
D. Feillet, P. Dejax, M. Gendreau and C. Gueguen,
An exact algorithm for the elementary shortest path problem with resource constraints: Application to some vehicle routing problems, Networks, 44 (2004), 216-229.
doi: 10.1002/net.20033. |
[9] |
B. Fleischmann, The vehicle routing problem with multiple use of vehicles (technical report), Hamburg: Universität Hamburg, 1990. Google Scholar |
[10] |
Gurobi, Optimizer Reference Manual, Houston: Gurobi Optimization Inc., 2016. Google Scholar |
[11] |
F. Hernandez, D. Feillet, R. Giroudeau and O. Naud,
A new exact algorithm to solve the multi-trip vehicle routing problem with time windows and limited duration, 4OR, 12 (2014), 235-259.
doi: 10.1007/s10288-013-0238-z. |
[12] |
IBM ILOG CPLEX Optimizer, IBM Corporation, New York, USA, accessed 17 April 2016,<http://www.ibm.com/software/commerce/optimization/cplex-optimizer> Google Scholar |
[13] |
IBM ILOG CPLEX Optimization Studio CPLEX User's Manual, New York, IBM Corporation, 2014. Google Scholar |
[14] |
R. Macedo, C. Alves, J. M. Valério de Carvalho, F. Clautiaux and S. Hanafi,
Solving the vehicle routing problem with time windows and multiple routes exactly using a pseudo-polynomial model, European Journal of Operational Research, 214 (2011), 536-545.
doi: 10.1016/j.ejor.2011.04.037. |
[15] |
A. Olivera and O. Viera,
Adaptive memory programming for the vehicle routing problem with multiple trips, Computers and Operations Research, 34 (2007), 28-47.
doi: 10.1016/j.cor.2005.02.044. |
[16] |
R. J. Petch and S. Salhi,
A multi-phase constructive heuristic for the vehicle routing problem with multiple trips, Discrete Applied Mathematics, 133 (2003), 69-92.
doi: 10.1016/S0166-218X(03)00434-7. |
[17] |
E. D. Taillard, G. Laporte and G. Gendreau, Vehicle routeing with multiple use of vehicles, Journal of the Operational Research Society, 47 (1996), 1065-1070. Google Scholar |
[18] |
P. Toth and D. Vigo, editors, The Vehicle Routing Problem, Philadelphia: SIAM, 2002.
doi: 10.1137/1.9780898718515. |
[19] |
S. Salhi and R. J. Petch,
A GA based heuristic for the vehicle routing problem with multiple trips, Journal of Mathematical Modelling and Algorithms, 6 (2007), 591-613.
doi: 10.1007/s10852-007-9069-2. |
[20] |
A. Şen and K. Bülbül, A survey on multi trip vehicle routing problem, In: Proceedings of the International Logistics and Supply Chain Congress 2008, Istanbul, Turkey. Google Scholar |
show all references
References:
[1] |
AIMMS Modelling Platform, AIMMS B. V., Haarlem, Netherlands, accessed 17 April 2016, <http://www.aimms.com> Google Scholar |
[2] |
F. Alonso, M. J. Alvarez and J. E. Beasley, A tabu search algorithm for the periodic vehicle routing problem with multiple vehicle trips and accessibility restrictions, Journal of the Operational Research Society, 59 (2008), 963-976. Google Scholar |
[3] |
N. Azi, M. Gendreau and J. Y. Potvin,
An exact algorithm for a single-vehicle routing problem with time windows and multiple routes, European Journal of Operational Research, 178 (2007), 755-766.
doi: 10.1016/j.ejor.2006.02.019. |
[4] |
N. Azi, M. Gendreau and J. Y. Potvin, An exact algorithm for a vehicle routing problem with time windows and multiple use of vehicles, European Journal of Operational Research, 202 (2010), 756-763. Google Scholar |
[5] |
M. Battarra, M. Monaci and D. Vigo, An adaptive guidance approach for the heuristic solution of a minimum multiple trip vehicle routing problem, Computers and Operations Research, 36 (2009), 3041-3050. Google Scholar |
[6] |
J. Bisschop, AIMMS Optimization Modelling, Haarlem: AIMMS B. V., 2016. Google Scholar |
[7] |
J. C. S. Brandão and A. Mercer, The multi-trip vehicle routing problem, Journal of the Operational Research Society, 49 (1998), 799-805. Google Scholar |
[8] |
D. Feillet, P. Dejax, M. Gendreau and C. Gueguen,
An exact algorithm for the elementary shortest path problem with resource constraints: Application to some vehicle routing problems, Networks, 44 (2004), 216-229.
doi: 10.1002/net.20033. |
[9] |
B. Fleischmann, The vehicle routing problem with multiple use of vehicles (technical report), Hamburg: Universität Hamburg, 1990. Google Scholar |
[10] |
Gurobi, Optimizer Reference Manual, Houston: Gurobi Optimization Inc., 2016. Google Scholar |
[11] |
F. Hernandez, D. Feillet, R. Giroudeau and O. Naud,
A new exact algorithm to solve the multi-trip vehicle routing problem with time windows and limited duration, 4OR, 12 (2014), 235-259.
doi: 10.1007/s10288-013-0238-z. |
[12] |
IBM ILOG CPLEX Optimizer, IBM Corporation, New York, USA, accessed 17 April 2016,<http://www.ibm.com/software/commerce/optimization/cplex-optimizer> Google Scholar |
[13] |
IBM ILOG CPLEX Optimization Studio CPLEX User's Manual, New York, IBM Corporation, 2014. Google Scholar |
[14] |
R. Macedo, C. Alves, J. M. Valério de Carvalho, F. Clautiaux and S. Hanafi,
Solving the vehicle routing problem with time windows and multiple routes exactly using a pseudo-polynomial model, European Journal of Operational Research, 214 (2011), 536-545.
doi: 10.1016/j.ejor.2011.04.037. |
[15] |
A. Olivera and O. Viera,
Adaptive memory programming for the vehicle routing problem with multiple trips, Computers and Operations Research, 34 (2007), 28-47.
doi: 10.1016/j.cor.2005.02.044. |
[16] |
R. J. Petch and S. Salhi,
A multi-phase constructive heuristic for the vehicle routing problem with multiple trips, Discrete Applied Mathematics, 133 (2003), 69-92.
doi: 10.1016/S0166-218X(03)00434-7. |
[17] |
E. D. Taillard, G. Laporte and G. Gendreau, Vehicle routeing with multiple use of vehicles, Journal of the Operational Research Society, 47 (1996), 1065-1070. Google Scholar |
[18] |
P. Toth and D. Vigo, editors, The Vehicle Routing Problem, Philadelphia: SIAM, 2002.
doi: 10.1137/1.9780898718515. |
[19] |
S. Salhi and R. J. Petch,
A GA based heuristic for the vehicle routing problem with multiple trips, Journal of Mathematical Modelling and Algorithms, 6 (2007), 591-613.
doi: 10.1007/s10852-007-9069-2. |
[20] |
A. Şen and K. Bülbül, A survey on multi trip vehicle routing problem, In: Proceedings of the International Logistics and Supply Chain Congress 2008, Istanbul, Turkey. Google Scholar |







Algorithm 1 Returns the value of |
Set |
Set |
while |
Set |
if |
Set |
return |
else if |
Set |
end if |
end while |
Set |
return |
Algorithm 1 Returns the value of |
Set |
Set |
while |
Set |
if |
Set |
return |
else if |
Set |
end if |
end while |
Set |
return |
Karratha | Angel | Goodwyn | Nganhurra | Ngujima-Yin | North Rankin | Okha | Pluto | |
Karratha | - | 68.4 | 78.4 | 180.0 | 175.0 | 75.0 | 65.0 | 95.9 |
Angel | 68.4 | - | 38.4 | 188.4 | 181.7 | 27.5 | 10.0 | 75.0 |
Goodwyn | 78.4 | 38.4 | - | 155.0 | 155.9 | 12.5 | 30.0 | 38.4 |
Nganhurra | 180.0 | 188.4 | 155.0 | - | 5.0 | 165.0 | 170.0 | 117.5 |
Ngujima-Yin | 175.0 | 181.7 | 155.9 | 5.0 | - | 160.0 | 165.0 | 112.5 |
North Rankin | 75.0 | 27.5 | 12.5 | 165.0 | 160.0 | - | 18.4 | 50.0 |
Okha | 65.0 | 10.0 | 30.0 | 170.0 | 165.0 | 18.4 | - | 65.0 |
Pluto | 95.9 | 75.0 | 38.4 | 117.5 | 112.5 | 50.0 | 65.0 | - |
Karratha | Angel | Goodwyn | Nganhurra | Ngujima-Yin | North Rankin | Okha | Pluto | |
Karratha | - | 68.4 | 78.4 | 180.0 | 175.0 | 75.0 | 65.0 | 95.9 |
Angel | 68.4 | - | 38.4 | 188.4 | 181.7 | 27.5 | 10.0 | 75.0 |
Goodwyn | 78.4 | 38.4 | - | 155.0 | 155.9 | 12.5 | 30.0 | 38.4 |
Nganhurra | 180.0 | 188.4 | 155.0 | - | 5.0 | 165.0 | 170.0 | 117.5 |
Ngujima-Yin | 175.0 | 181.7 | 155.9 | 5.0 | - | 160.0 | 165.0 | 112.5 |
North Rankin | 75.0 | 27.5 | 12.5 | 165.0 | 160.0 | - | 18.4 | 50.0 |
Okha | 65.0 | 10.0 | 30.0 | 170.0 | 165.0 | 18.4 | - | 65.0 |
Pluto | 95.9 | 75.0 | 38.4 | 117.5 | 112.5 | 50.0 | 65.0 | - |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Ngujima-Yin | 1 | 300 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 2 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 2 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 3 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 6 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 6 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 8 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 9 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 10 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 16 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 16 | 300 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 16 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 19 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 20 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 20 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Ngujima-Yin | 1 | 300 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 2 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 2 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 3 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 6 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 6 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 8 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 9 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 10 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 16 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 16 | 300 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 16 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 19 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 20 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 20 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Goodwyn | 1 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 2 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 5 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 5 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 5 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 6 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 8 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 9 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Okha | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 13 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 14 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 15 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 18 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Goodwyn | 1 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 2 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 5 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 5 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 5 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 6 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 8 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 9 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 9 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Okha | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 13 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 14 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 15 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 18 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Angel | 1 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 3 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Angel | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 4 | 100 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 5 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 8 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 8 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 8 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 10 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 11 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 14 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 14 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 15 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 21 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 21 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Angel | 1 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 3 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Angel | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 4 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 4 | 100 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 5 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 7 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 8 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 8 | 200 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 8 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 10 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 11 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 12 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 14 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 14 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 15 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 17 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 19 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 21 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 21 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Goodwyn | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 1 | 250 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 4 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 5 | 150 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 7 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 7 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 8 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 9 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 10 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 11 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 12 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 13 | 100 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 15 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 16 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 17 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Angel | 21 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 21 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Facility | Day | Demand | Time Window | Duration | Suitable Vessels | Off-take? |
Goodwyn | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 1 | 250 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
North Rankin | 1 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 3 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 4 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 5 | 150 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 7 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 7 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 8 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 9 | 250 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 10 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 11 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 11 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Pluto | 12 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 13 | 100 m2 | 0:00-24:00 | 30 hours | OSV | Yes |
Goodwyn | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 14 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 15 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 16 | 200 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Ngujima-Yin | 17 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Goodwyn | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Nganhurra | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
North Rankin | 18 | 150 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Angel | 21 | 300 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Okha | 21 | 100 m2 | 0:00-24:00 | 3 hours | PSV, OSV | No |
Original Model | Simplified Model | ||||||
BVs | CVs | Constraints | BVs | CVs | Constraints | ||
Scenario 1 | 1,646,568 | 1,646,569 | 1,646,870 | 206,868 | 20,571 | 207,167 | |
Scenario 2 | 2,069,928 | 2,069,929 | 2,070,258 | 292,443 | 31,582 | 292,771 | |
Scenario 3 | 2,541,672 | 2,541,673 | 2,542,030 | 322,105 | 35,540 | 322,461 | |
Scenario 4 | 2,795,688 | 2,795,689 | 2,796,060 | 330,484 | 39,859 | 330,853 |
Original Model | Simplified Model | ||||||
BVs | CVs | Constraints | BVs | CVs | Constraints | ||
Scenario 1 | 1,646,568 | 1,646,569 | 1,646,870 | 206,868 | 20,571 | 207,167 | |
Scenario 2 | 2,069,928 | 2,069,929 | 2,070,258 | 292,443 | 31,582 | 292,771 | |
Scenario 3 | 2,541,672 | 2,541,673 | 2,542,030 | 322,105 | 35,540 | 322,461 | |
Scenario 4 | 2,795,688 | 2,795,689 | 2,796,060 | 330,484 | 39,859 | 330,853 |
Total Fuel Use (L) | ||||
Historical | Initial | Optimized | Improvement | |
Scenario 1 | 108,620 | 107,560 | 97,440 | 10.29% |
Scenario 2 | 124,460 | 113,880 | 96,040 | 22.83% |
Scenario 3 | 139,500 | 138,400 | 125,820 | 9.81% |
Scenario 4 | 170,680 | 168,960 | 148,640 | 12.91% |
Total Fuel Use (L) | ||||
Historical | Initial | Optimized | Improvement | |
Scenario 1 | 108,620 | 107,560 | 97,440 | 10.29% |
Scenario 2 | 124,460 | 113,880 | 96,040 | 22.83% |
Scenario 3 | 139,500 | 138,400 | 125,820 | 9.81% |
Scenario 4 | 170,680 | 168,960 | 148,640 | 12.91% |
Deck-space Utilization | Time Utilization | ||||||
PSV | OSV 1 | OSV 2 | PSV | OSV 1 | OSV 2 | ||
Scenario 1 | 100% | 100% | 100% | 30% | 37% | 31% | |
Scenario 2 | 80% | 88% | 89% | 26% | 31% | 31% | |
Scenario 3 | 100% | 78% | 83% | 51% | 33% | 27% | |
Scenario 4 | 92% | 96% | 100% | 45% | 41% | 43% |
Deck-space Utilization | Time Utilization | ||||||
PSV | OSV 1 | OSV 2 | PSV | OSV 1 | OSV 2 | ||
Scenario 1 | 100% | 100% | 100% | 30% | 37% | 31% | |
Scenario 2 | 80% | 88% | 89% | 26% | 31% | 31% | |
Scenario 3 | 100% | 78% | 83% | 51% | 33% | 27% | |
Scenario 4 | 92% | 96% | 100% | 45% | 41% | 43% |
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