TOOLS FOR ASSISTING IN PETROLEUM PRODUCT TRANSPORTATION LOGISTICS
First Claim
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1. A method for transporting bulk products, comprising:
- (I) receiving a data set comprising;
(a) an identification of a plurality of supply locations and a plurality of demand locations;
(b) for each supply location, identification of one or more supply streams of bulk products and the monetary values of the bulk products from the supply stream;
(c) for each demand location, identification of one or more demand streams of bulk products and the monetary values of the bulk products that meet the property specification requirements of the demand stream;
(d) identification of a fleet of vehicles for carrying bulk products between supply locations and demand locations;
(e) data relating to the capacity of each vehicle in the fleet;
(f) data relating to the costs for transporting bulk products from the supply locations to the demand locations; and
(g) identification of one or more blending tanks located at a demand location or a supply location for receiving bulk product from a vehicle and discharging bulk product to a demand stream;
(II) using the data set to populate a mathematical model that comprises an objective function for net profit margin and a plurality of constraints;
wherein the constraints include one or more non-linear terms relating to the quantity or property of blending tank content;
(III) obtaining a solution to the mathematical model for maximizing the objective function for net profit margin; and
(IV) physically transporting one or more bulk products based on the solution to the mathematical model.
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Abstract
A tool to assist decision-making in the logistics of bulk product transportation. For example, the tool may be used to solve a problem involving the transportation and the inventory management of crude oil, in which the transportation of crude oil between supply ports and discharge ports are performed by a fleet of ships. The tool is capable of handling a typical petroleum product transportation problem, which can be quite complex. The tool uses advanced modeling and optimization technology to find a solution (either optimal or near optimal) for the allocation of bulk products, vehicle routing, vehicle scheduling, and/or bulk product blending operations.
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Citations
28 Claims
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1. A method for transporting bulk products, comprising:
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(I) receiving a data set comprising; (a) an identification of a plurality of supply locations and a plurality of demand locations; (b) for each supply location, identification of one or more supply streams of bulk products and the monetary values of the bulk products from the supply stream; (c) for each demand location, identification of one or more demand streams of bulk products and the monetary values of the bulk products that meet the property specification requirements of the demand stream; (d) identification of a fleet of vehicles for carrying bulk products between supply locations and demand locations; (e) data relating to the capacity of each vehicle in the fleet; (f) data relating to the costs for transporting bulk products from the supply locations to the demand locations; and (g) identification of one or more blending tanks located at a demand location or a supply location for receiving bulk product from a vehicle and discharging bulk product to a demand stream; (II) using the data set to populate a mathematical model that comprises an objective function for net profit margin and a plurality of constraints; wherein the constraints include one or more non-linear terms relating to the quantity or property of blending tank content; (III) obtaining a solution to the mathematical model for maximizing the objective function for net profit margin; and (IV) physically transporting one or more bulk products based on the solution to the mathematical model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. An computer apparatus for determining the transportation of bulk products, comprising:
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(I) a memory device storing a data file containing; (a) an identification of a plurality of supply locations and a plurality of demand locations; (b) for each supply location, identification of one or more supply streams of bulk products and the monetary values of the bulk products from the supply stream; (c) for each demand location, identification of one or more demand streams of bulk products and the monetary values of the bulk products that meet the property specification requirements of the demand stream; (d) identification of a fleet of vehicles for carrying bulk products between supply locations and demand locations; (e) data relating to the capacity of each vehicle in the fleet; (f) data relating to the costs for transporting bulk products from the supply locations to the demand locations; and (g) identification of one or more blending tanks located at a demand location or a supply location for receiving bulk product from a vehicle and discharging bulk product to a demand stream; (II) a modeling application executable by the optimization apparatus to populate a mathematical model using the data file, the mathematical model comprising an objective function for net profit margin and a plurality of constraints; wherein the constraints include one or more non-linear terms relating to the quantity or property of blending tank content; (III) a solver engine operable by the optimization apparatus to obtain a solution to the mathematical model for maximizing the objective function for net profit margin.
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28. A program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform method steps for determining the transportation of bulk products, said method steps comprising:
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(I) reading a data file comprising; (a) an identification of a plurality of supply locations and a plurality of demand locations; (b) for each supply location, identification of one or more supply streams of bulk products and the monetary values of the bulk products from the supply stream; (c) for each demand location, identification of one or more demand streams of bulk products and the monetary values of the bulk products that meet the property specification requirements of the demand stream; (d) identification of a fleet of vehicles for carrying bulk products between supply locations and demand locations; (e) data relating to the capacity of each vehicle in the fleet; (f) data relating to the costs for transporting bulk products from the supply locations to the demand locations; and (g) identification of one or more blending tanks located at a demand location or a supply location for receiving bulk product from a vehicle and discharging bulk product to a demand stream; (II) using the data file to populate a mathematical model that comprises an objective function for net profit margin and a plurality of constraints; wherein the constraints include one or more non-linear terms relating to the quantity or property of blending tank content; (III) obtaining a solution to the mathematical model for maximizing the objective function for net profit margin.
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Specification