CN111080052A - Berth scheduling optimization method and system suitable for refinery plant - Google Patents
Berth scheduling optimization method and system suitable for refinery plant Download PDFInfo
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Abstract
The invention relates to the field of industrial production scheduling, in particular to a berth scheduling optimization method and a berth scheduling optimization system suitable for a refinery, which comprise the following steps: acquiring oil tanker data and berth data; establishing a parking space scheduling general model by taking the minimum lag cost as a target; on the basis of the general model of the berth dispatching, selecting the adopted constraint condition according to the actual business requirement, and further generating a berth dispatching optimization model; and calling the berth dispatching optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth dispatching plan. The invention has the following beneficial effects: the method comprehensively considers various constraints such as berth, oil tanker, service, weather and the like, and realizes the optimized arrangement of the oil tanker operation berth and operation time in a period in the future by establishing a berth scheduling optimization model, thereby ensuring stable and safe production of enterprises and effectively reducing the lag cost so as to improve the production benefit of the enterprises.
Description
Technical Field
The invention relates to the field of industrial production scheduling, in particular to a berth scheduling optimization method and a berth scheduling optimization system suitable for a refinery.
Background
Transportation of oil products in and out of a factory is a key link of production scheduling and production scheduling of petrochemical oil refining enterprises, wherein sea transportation is a main transportation mode of most of crude oil and finished oil. Due to the limited berth resources, the operation berthing and the operation time of the oil tanker which transports goods by sea need to be reasonably arranged on the basis of the existing berthing quantity, and the berth dispatching operation plan is worked out.
At present, the berth planning of petrochemical oil refining enterprises is mainly based on the traditional first-come-first-serve principle, which causes the unsatisfied and frequent switching of the processing scheme plan of the device, cannot ensure the stable production of refineries and can bring about safety problems in serious cases; or only considering the requirements of the device processing scheme on oil products, the oil ship with key oil products is considered preferentially, and the oil ship with non-key oil products is not considered too much, so that a great amount of loss of the lag time cost cannot be avoided. In addition, the traditional berth planning method is greatly influenced by subjective factors, and scheduling and production scheduling personnel depend on personal prior knowledge and lack of profit optimization calculation and global consideration.
Disclosure of Invention
In order to solve the above problems, the present invention provides a berth scheduling optimization method and system suitable for a refinery.
A berth scheduling optimization method suitable for a refinery plant comprises the following steps:
acquiring oil tanker data and berth data;
establishing a general berth scheduling model by taking minimum lag cost as a target:
sjf_x2(i,4)>＝sjf_x2(i,2)，
where C represents the hysteresis coefficient for each ship, sjf _ x2iThe scheduling operation arrangement of the oil tanker at the i berth is shown, and free _ hours show the free operation time length of each oil tanker;
on the basis of the general model of the berth dispatching, selecting the adopted constraint condition according to the actual business requirement, and further generating a berth dispatching optimization model;
and calling the berth dispatching optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth dispatching plan.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (4) priority range constraint: and matching the oil type data set loaded by the oil tanker with the prior oil type, recording the matched voyage number, and expanding the matched voyage number into the prior voyage number data set.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (3) restriction of the oil seeds at the berth: the oil type loaded by the tanker must be the type allowed for the berth.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (3) load capacity constraint: the tanker load must be less than the maximum load at its operating berth.
Preferably, the method further comprises the following steps:
and acquiring weather data and tide data, delaying the arrival time of the affected oil tanker, determining the delayed time length according to the weather data and the tide data, and updating the berth dispatching plan.
A berthing scheduling optimization system suitable for a refinery, comprising:
the data acquisition module is used for acquiring oil tanker data and berth data;
the model establishing module is used for establishing a general berth dispatching model by taking the minimum delay charge as a target:
sjf_x2(i,4)>＝sjf_x2(i,2)，
where C represents the hysteresis coefficient for each ship, sjf _ x2iScheduling of tanker scheduling jobs, free _ hou, representing i berthsrs represents the free operation time length of each ship;
the model optimization module is used for selecting adopted constraint conditions according to actual business requirements on the basis of the general model for berth scheduling and further generating a berth scheduling optimization model;
and the model calculation module is used for calling the berth scheduling optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth scheduling plan.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (4) priority range constraint: and matching the oil type data set loaded by the oil tanker with the prior oil type, recording the matched voyage number, and expanding the matched voyage number into the prior voyage number data set.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (3) restriction of the oil seeds at the berth: the oil type loaded by the tanker must be the type allowed for the berth.
Preferably, on the basis of the general model for berth scheduling, selecting the adopted constraint condition according to the actual service requirement includes:
and (3) load capacity constraint: the tanker load must be less than the maximum load at its operating berth.
Preferably, the model calculation module is further configured to acquire weather data and tide data, delay an arrival time of the affected tanker, determine a delayed time length according to the weather data and the tide data, and update the berth scheduling plan.
The invention has the following beneficial effects: the method comprehensively considers various constraints such as berth, oil tanker, service, weather and the like, and realizes the optimized arrangement of the oil tanker operation berth and operation time in a period in the future by establishing a berth scheduling optimization model, thereby ensuring stable and safe production of enterprises and effectively reducing the lag cost so as to improve the production benefit of the enterprises.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a schematic flow chart of a berth scheduling optimization method for a refinery according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating step S5 of the berth scheduling optimization method for a refinery according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a berth dispatching optimization system suitable for a refinery according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a result display module in the berthing dispatching optimization system suitable for a refinery according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be further described below with reference to the accompanying drawings, but the present invention is not limited to these embodiments.
The basic idea of the embodiment is to comprehensively consider various constraints such as berth, oil tanker, service, weather and the like, and realize the optimized arrangement of the oil tanker operation berth and operation time in a period in the future by establishing a berth scheduling optimization model, thereby ensuring stable and safe production of enterprises and effectively reducing the lag time cost so as to improve the production benefits of the enterprises.
Based on the above thought, an embodiment of the present invention provides a berth scheduling optimization method suitable for a refinery plant, as shown in fig. 1, including the following steps:
s1: acquiring oil tanker data and berth data;
s2: establishing a parking space scheduling general model by taking the minimum lag cost as a target;
s3: on the basis of the general model of the berth dispatching, selecting the adopted constraint condition according to the actual business requirement, and further generating a berth dispatching optimization model;
s4: and calling the berth dispatching optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth dispatching plan.
The oil tanker data comprises arrival plans of oil tankers and basic attribute data of the oil tankers; the berth data comprises operation state data, oil product priority data, voyage priority data, limitation of berth on oil product types, limitation of berth loading capacity and limitation of berth on oil ships. The arrival plan of the oil tanker comprises a ship name, arrival time, operation time, actual operation starting time, actual operation finishing time, actual total residence time and authorized residence time.
The berth dispatching optimization method simplifies the berth dispatching problem into a form of embedding a tanker dispatching sub-problem in the berth distribution problem, and establishes a semi-heuristic general berth dispatching model by taking minimum lag cost as a target:
sjf_x2(i,4)>＝sjf_x2(i,2)，
where C represents the coefficient of the delay charge per ship (ten thousand yuan/hour), sjf _ x2iThe scheduling operation arrangement of the oil tanker representing the i berth comprises a ship name, arrival time, operation time, actual operation starting time, actual operation completing time, actual total stay time and authorized stay time, free _ hours represents the free operation time length of each ship, and the lag fee is calculated when the free operation time length exceeds the limit value. The general model for the berthage scheduling is established by adopting a semi-heuristic method, and compared with an ant colony algorithm, a genetic algorithm and the like, the model is high in solving efficiency and high in feasibility of a calculation result.
Various constraints such as berth, oil tanker, service and the like are considered, constraint conditions adopted by actual service requirements are selected on the basis of the original general berth scheduling model, a berth scheduling optimization model is generated, optimal arrangement of oil tanker operation berth and operation time in a period in the future is realized, stable and safe production of enterprises is guaranteed, and meanwhile, delay cost is effectively reduced, so that production benefits of the enterprises are improved.
The constraint conditions in this embodiment include:
and (4) priority range constraint: firstly, screening out a priority voyage according to a priority oil type name, matching an oil type data set loaded by an oil tanker with the priority oil type, recording a matched voyage number, and expanding the matched voyage number data into the priority voyage number data set. And secondly, acquiring a voyage priority data set, merging the voyage priority data set with the priority voyage data acquired by the priority oil type, and acquiring a new priority voyage data set as a constraint.
Limiting variables: and setting a variable xij of the berth scheduling optimization model, wherein the variable is a 0 and 1 value variable and indicates whether the j tanker is stopped at i berths, wherein i is 1, 2.
The operation constraint is that all arriving tankers must operate once.
And (3) restriction of the oil seeds at the berth: the oil type loaded by the tanker must be the type allowed for the berth.
And (3) load capacity constraint: the tanker load must be less than the maximum load at its operating berth.
Draft depth restraint: the tanker draft must be less than the maximum allowable tanker draft for its operating berth. If the tide height data acquired in real time exceeds a set threshold value A (the threshold value is set by user experience and is 300cm by default), adding a coefficient C (the coefficient B, C is set by user experience and is 2 and 300cm by default) to the draught of the oil tanker operated in B days later at that time, and recalling the model optimization calculation.
And (4) restraining the captain: the tanker should select a berth that can accept the length of its hull for operation.
The constraint conditions can be manually selected according to actual business requirements, so that the berth dispatching plan calculated according to the berth dispatching optimization model is more in line with the actual requirements.
And acquiring the oil tanker data and the oil tanker arrival plan in the berth data and the berth running state data before the beginning of the dispatching cycle, calling the berth dispatching optimization model, and calculating to obtain a berth dispatching plan. The berthage dispatching plan is obtained through automatic optimization calculation, and compared with a manually made dispatching plan, the berthage dispatching plan can obviously reduce the delay cost.
As shown in fig. 2, the method includes the steps of:
s5: and acquiring weather data and tide data, delaying the arrival time of the affected oil tanker, determining the delayed time length according to the weather data and the tide data, and updating the berth dispatching plan.
The weather con constraint may be set at this time because of the possibility of delayed arrival for some tankers due to special weather such as typhoons. The weather Con is a value restriction of 0 and 1, and the length is equal to the length of the scheduling period. For example, a scheduling period of 1-7 days, where there may be typhoon weather on days 4-6 in the future, then: adjusting the arrival plan of the tanker on the 4 th to 6 th days according to the weather Con [ 0001110 ], specifically adding a lag coefficient wd to the arrival time of the tanker, defaulting to 2 days, and recalling the model optimization calculation. The uncertainty of the arrival time of the oil tanker is considered, and the model can automatically adjust the arrival time of the voyage affected by bad weather or tidal altitude according to a preset special condition processing method.
Based on the foregoing method for optimizing berth scheduling applicable to a refinery, in terms of hardware, as shown in fig. 3, the embodiment further provides a berth scheduling optimization system applicable to a refinery, including: the data acquisition module is used for acquiring oil tanker data and berth data; the model establishing module is used for establishing a general berth dispatching model by taking the minimum delay charge as a target; the model optimization module is used for selecting adopted constraint conditions according to actual business requirements on the basis of the general model for berth scheduling and further generating a berth scheduling optimization model; and the model calculation module is used for calling the berth scheduling optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth scheduling plan.
And collecting data such as arrival plan of the oil tanker, actual operation data of berthing, weather, tidal height and the like. Wherein, the oil tanker arrival plan data source is manually imported or an MES report is obtained; acquiring actual operation data of the berth by an MES system; weather information is acquired by a webpage; the tidal height data is acquired by a maritime service network.
The model building module simplifies the berth scheduling problem into a form of embedding a tanker scheduling subproblem in the berth distribution problem, and builds a semi-heuristic general berth scheduling model by taking minimum delay cost as a target:
sjf_x2(i,4)>＝sjf_x2(i,2)，
where C represents the coefficient of the delay charge per ship (ten thousand yuan/hour), sjf _ x2iThe scheduling operation arrangement of the oil tanker representing the i berth comprises a ship name, arrival time, operation time, actual operation starting time, actual operation completing time, actual total stay time and authorized stay time, free _ hours represents the free operation time length of each ship, and the lag fee is calculated when the free operation time length exceeds the limit value. The general model for the berthage scheduling is established by adopting a semi-heuristic method, and compared with an ant colony algorithm, a genetic algorithm and the like, the model is high in solving efficiency and high in feasibility of a calculation result.
Various constraints such as berth, oil tanker, service and the like are considered, constraint conditions adopted by actual service requirements are selected on the basis of the original general berth scheduling model, a berth scheduling optimization model is generated, optimal arrangement of oil tanker operation berth and operation time in a period in the future is realized, stable and safe production of enterprises is guaranteed, and meanwhile, delay cost is effectively reduced, so that production benefits of the enterprises are improved.
The constraint conditions in this embodiment include: the method comprises the following steps of preferential voyage constraint, variable limitation, operation constraint, berth oil seed constraint, loading capacity constraint, draft constraint and captain constraint. The specific constraints have already been described in detail in the above method, and therefore are not described in detail here. The constraint conditions can be manually selected through the model optimization module, so that the berth dispatching plan calculated according to the berth dispatching optimization model is more in line with the actual requirements.
And acquiring the oil tanker data and the oil tanker arrival plan in the berth data and the berth running state data before the beginning of the dispatching cycle, calling the berth dispatching optimization model, and calculating to obtain a berth dispatching plan. The berthage dispatching plan is obtained through automatic optimization calculation, and compared with a manually made dispatching plan, the berthage dispatching plan can obviously reduce the delay cost.
Preferably, the model calculation module is further configured to acquire weather data and tide data, delay the arrival time of the affected tanker, determine the delayed time length according to the weather data and the tide data, and update the berth scheduling plan.
The weather con constraint may be set at this time because of the possibility of delayed arrival for some tankers due to special weather such as typhoons. The weather Con is a value restriction of 0 and 1, and the length is equal to the length of the scheduling period. For example, a scheduling period of 1-7 days, where there may be typhoon weather on days 4-6 in the future, then: adjusting the arrival plan of the tanker on the 4 th to 6 th days according to the weather Con [ 0001110 ], specifically adding a lag coefficient wd to the arrival time of the tanker, defaulting to 2 days, and recalling the model optimization calculation. The uncertainty of the arrival time of the oil tanker is considered, and the model can automatically adjust the arrival time of the voyage affected by bad weather or tidal altitude according to a preset special condition processing method.
As a preferred embodiment, as shown in fig. 4, the berth dispatching optimization system further includes a result display module, where the result display module visually presents an optimization result generated by the data calculation module on the display platform, and the display data includes a berth dispatching plan of a period in the future, an operation condition of a current berth, a comparison result between the berth dispatching plan and an actual operation result, expected late-term charge data, and the like. Meanwhile, the display platform can provide a historical job data query window.
In addition, the berth dispatching optimization system provides a human-computer interaction interface for users. The user can modify the berthage dispatching plan generated by the optimization model in a manual input mode, and the feasibility of the berthage dispatching plan is enhanced. And further pushing the manually corrected berth dispatching plan to a related personnel mailbox through issuing.
Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (10)
1. A berth scheduling optimization method suitable for a refinery plant is characterized by comprising the following steps:
acquiring oil tanker data and berth data;
establishing a general berth scheduling model by taking minimum lag cost as a target:
sjf_x2(i,4)＞＝sjf_x2(i,2)，
wherein, C represents the delay fee coefficient of each ship, sjf _ x2i represents the scheduling operation arrangement of the oil tanker in the i berth, and free _ hours represents the time length of free operation of each ship;
on the basis of the general model of the berth dispatching, selecting the adopted constraint condition according to the actual business requirement, and further generating a berth dispatching optimization model;
and calling the berth dispatching optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth dispatching plan.
2. The berth scheduling optimization method suitable for refineries according to claim 1, wherein the selecting constraints adopted according to actual business requirements on the basis of the general berth scheduling model comprises:
and (4) priority range constraint: and matching the oil type data set loaded by the oil tanker with the prior oil type, recording the matched voyage number, and expanding the matched voyage number into the prior voyage number data set.
3. The berth scheduling optimization method suitable for refineries according to claim 1, wherein the selecting constraints adopted according to actual business requirements on the basis of the general berth scheduling model comprises:
and (3) restriction of the oil seeds at the berth: the oil type loaded by the tanker must be the type allowed for the berth.
4. The berth scheduling optimization method suitable for refineries according to claim 1, wherein the selecting constraints adopted according to actual business requirements on the basis of the general berth scheduling model comprises:
and (3) load capacity constraint: the tanker load must be less than the maximum load at its operating berth.
5. The berth scheduling optimization method for a refinery according to claim 1, further comprising:
and acquiring weather data and tide data, delaying the arrival time of the affected oil tanker, determining the delayed time length according to the weather data and the tide data, and updating the berth dispatching plan.
6. A berthing scheduling optimization system suitable for a refinery, comprising:
the data acquisition module is used for acquiring oil tanker data and berth data;
the model establishing module is used for establishing a general berth dispatching model by taking the minimum delay charge as a target:
sjf_x2(i,4)＞＝sjf_x2(i,2)，
wherein, C represents the delay fee coefficient of each ship, sjf _ x2i represents the scheduling operation arrangement of the oil tanker in the i berth, and free _ hours represents the time length of free operation of each ship;
the model optimization module is used for selecting adopted constraint conditions according to actual business requirements on the basis of the general model for berth scheduling and further generating a berth scheduling optimization model;
and the model calculation module is used for calling the berth scheduling optimization model, importing the oil tanker data and the berth data, and calculating to obtain a berth scheduling plan.
7. The system of claim 6, wherein the selecting constraints according to actual business requirements based on the common model of berthing scheduling comprises:
and (4) priority range constraint: and matching the oil type data set loaded by the oil tanker with the prior oil type, recording the matched voyage number, and expanding the matched voyage number into the prior voyage number data set.
8. The system of claim 6, wherein the selecting constraints according to actual business requirements based on the common model of berthing scheduling comprises:
and (3) restriction of the oil seeds at the berth: the oil type loaded by the tanker must be the type allowed for the berth.
9. The system of claim 6, wherein the selecting constraints according to actual business requirements based on the common model of berthing scheduling comprises:
and (3) load capacity constraint: the tanker load must be less than the maximum load at its operating berth.
10. The refinery-applicable berth scheduling optimization system of claim 6, wherein the model computation module is further configured to obtain weather data and tidal data, delay the arrival time of the affected tanker, determine the delayed duration according to the weather data and the tidal data, and update the berth scheduling plan.
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