CN112249583B - Intelligent selection method and system for bulk cargo wharf stock yard stacking position - Google Patents

Intelligent selection method and system for bulk cargo wharf stock yard stacking position Download PDF

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CN112249583B
CN112249583B CN202011063403.2A CN202011063403A CN112249583B CN 112249583 B CN112249583 B CN 112249583B CN 202011063403 A CN202011063403 A CN 202011063403A CN 112249583 B CN112249583 B CN 112249583B
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stacking
ship
selection
stack
cargo
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CN112249583A (en
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吕长虹
杨立光
宣国宝
张小锐
李顺平
王超
成常杰
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East China Normal University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
    • B65G1/02—Storage devices
    • B65G1/04—Storage devices mechanical
    • B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
    • B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G63/00—Transferring or trans-shipping at storage areas, railway yards or harbours or in opening mining cuts; Marshalling yard installations
    • B65G63/002—Transferring or trans-shipping at storage areas, railway yards or harbours or in opening mining cuts; Marshalling yard installations for articles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G67/00—Loading or unloading vehicles
    • B65G67/60—Loading or unloading ships
    • B65G67/603—Loading or unloading ships using devices specially adapted for articles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
    • B65G2203/02—Control or detection
    • B65G2203/0208—Control or detection relating to the transported articles
    • B65G2203/0233—Position of the article
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
    • B65G2203/04—Detection means

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  • Mechanical Engineering (AREA)
  • Ocean & Marine Engineering (AREA)
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  • Ship Loading And Unloading (AREA)

Abstract

The invention discloses an intelligent selection method and system for bulk cargo wharf stock yard stacking positions, wherein the method comprises the following steps: acquiring stack selection data and preprocessing the stack selection data; constructing a stack position selection evaluation function according to the preprocessed stack selection data, and solving to obtain a stack selection result; constructing a stack order evaluation function according to the stack selection result, and solving to obtain a stack order; and selecting the stacking positions according to the stacking sequence. The system comprises: a user module; a calculation module; a stack position selection module; and a data statistics module. The method has the advantages that the stacking position selection and stacking sequence are automatically calculated, the calculation result is accumulated according to manual experience and data deposition, and planning personnel in charge of selecting the stacking position do not need years of work experience and professional ability, so that the enterprise cost is effectively reduced.

Description

Intelligent selection method and system for bulk cargo wharf stock yard stacking position
Technical Field
The invention relates to the field of port stacking position selection, in particular to an intelligent selection method and system for bulk cargo wharf yard stacking positions.
Background
As is known, in a yard of a terminal, different yards are selected for different cargoes, so that benefits of enterprises are different, a plurality of excellent algorithms are formed for optimizing a selected stacking position of a container terminal due to container regularity, and for a bulk cargo terminal, due to bulk cargo irregularity and irregular bulk cargo size, the algorithm of the container cannot be well optimized in the bulk cargo terminal. In the process of selecting the stacking position of the port and the wharf, the selection is mainly judged according to the manual work at the present stage, and the optimal result cannot be selected.
Aiming at the problem of selecting the stacking position of the bulk cargo wharf, the main mode is based on manual experience at present, the stacking position is manually selected, the stacking mode is related to the difference of the experience of people, and the good stacking position can not be selected every time. Nor is a specific evaluation criterion for the stack selection results given.
Therefore, an intelligent selection algorithm for bulk cargo wharf yard stacking positions and a corresponding evaluation system are needed to be provided, and based on the evaluation system, manual stacking position selection can be optimized, so that the enterprise cost is reduced, and the enterprise profit is increased.
Disclosure of Invention
In view of the defects, the invention provides the intelligent selection method and the system for the bulk cargo wharf stock yard stock space, which can automatically calculate a scientific and reasonable plan scheme, improve the service level of a port dispatching department and enable a port to develop towards the intellectualization direction.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
an intelligent selection method for bulk cargo wharf stock yard pile positions comprises the following steps:
acquiring stack selection data and preprocessing the stack selection data;
constructing a stack position selection evaluation function according to the preprocessed stack selection data, and solving to obtain a stack selection result;
constructing a stack order evaluation function according to the stack selection result, and solving to obtain a stack order;
and selecting the stacking positions according to the stacking sequence.
According to one aspect of the invention, the stack selection data comprises ship information, ship cargo information, dock information and weather information.
According to one aspect of the invention, the pre-processing of the stack selection data is specifically: defining parameter values according to the stack selection data; and evaluating the matching score of the goods and the stacking position according to the ship information, the ship goods information, the wharf information, the weather information and the weight given by the manual or system.
According to one aspect of the invention, the terminal comprises BDQs which are conveyors from berths where ships dock to stockyard berths, each BDQ being available for only one ship at a time.
In accordance with one aspect of the invention, the berth selection assessment function is:
Figure BDA0002713012350000021
wherein the parameters include: whether the ith ship selects the jth stacking position a ij E, e.g. 0,1, selecting a value of 1, and selecting a value of 0 without selecting;
the amount z of cargo to be distributed by the kth ship on the 1 st track kl ≥0；
The amount yard of goods available for the s-th stack space s ；
The number n of ships;
match Score of ith ship at jth stacking position Score ij ；
Quantity SizeNeed of cargo required for ith ship i ；
The number m of the stack positions;
the number r of BDQs;
meanwhile, the stacking position conditions to be met are as follows:
Figure BDA0002713012350000022
Figure BDA0002713012350000023
Figure BDA0002713012350000024
Figure BDA0002713012350000025
Figure BDA0002713012350000026
the significance lies in that: the number of the stacking positions is q, and the condition 1 is that each stacking position is only allocated to one ship; condition 2 is that the number of piles to which each vessel can be allocated cannot exceed w; condition 3 is that the amount of cargo to be accommodated in the pile space allocated to each ship is equal to or greater than the required amount of cargo; condition 4 is the allocation of the first BDQ for the ith ship, penalizing if the recommended cargo amount given is exceeded; condition 5 is that the s BDQ usage time of the i-th ship is equal to or less than the available time.
According to one aspect of the invention, the method of combining the branch definition method and the plane cutting method is adopted to solve the stacking position selection evaluation function, and all a which enable the score of the stacking position selection evaluation function to be highest and meet the stacking position condition are solved ij I.e. the result of the selection of a particular ship.
According to one aspect of the invention, the stacking order assessment function is:
Figure BDA0002713012350000031
Figure BDA0002713012350000032
Figure BDA0002713012350000033
Figure BDA0002713012350000034
Figure BDA0002713012350000035
y ij ≥M*y i1 j＝13，…，18
Figure BDA0002713012350000036
Figure BDA0002713012350000037
wherein the parameters include: recommended cargo quantity BDQccupy given by jth BDQ of ith ship under condition of average residual mass ij ；
The jth BDQ available time BDQtime of the ith ship ij ；
Arrival time T of ith ship istart ；
Departure time T of ith ship istart ；
Cargo volume m of ith ship i ；
Stacking sequence symbols:
0-1 parameter y for the ith ship ij ∈{0，1}，1≤j≤12；
Continuous variable y of ith ship ij ，13≤j≤18；
Starting variable y of ith ship ij J is more than or equal to 19 and less than or equal to 24, which means that the ith ship is supposed to have 3 BDQs available and can not be used simultaneously with each other, and the working time of the BDQ1 is [ y [) i19 ，y i20 ]BDQ2 has a working time of y i21 ，y i22 ]BDQ3 has a working time of y i23 ，y i24 ]。
According to one aspect of the invention, after the stack selection result is obtained, the position of the stack position corresponding to each ship is obtained, and the stacking sequence evaluation function is solved by traversing all stacking operation sequences to obtain the optimal stacking sequence.
According to one aspect of the invention, the method further comprises the following steps: and storing the stacking sequence results in a database, and forming a data statistics module through a statistics device.
An intelligent selection system for bulk cargo wharf stock yard stock position, the intelligent selection method and system for the stacking position of the storage yard comprises the following steps:
the user module comprises a data input device and a parameter modifier, wherein the data input device is used for inputting stack selection data, and the parameter modifier is used for adjusting data parameters;
the calculating module comprises a stacking position selector and a stacking sequencer, the stacking position selector is used for constructing a stacking position selection evaluation function to obtain a stacking selection result, and the stacking sequencer is used for constructing a stacking sequence evaluation function to obtain a stacking sequence;
and the stacking position selection module is used for selecting the stacking positions according to the stacking sequence.
The implementation of the invention has the advantages that: the invention discloses an intelligent selection method and system for bulk cargo wharf stock yard stacking positions, wherein the method comprises the following steps: acquiring stack selection data and preprocessing the stack selection data; constructing a stack position selection evaluation function according to the preprocessed stack selection data, and solving to obtain a stack selection result; constructing a stack sequence evaluation function according to the stack selection result, and solving to obtain a stack sequence; and selecting the stacking positions according to the stacking sequence. The system comprises: a user module; a calculation module; a stack position selection module; and a data statistics module. The method has the advantages that the stacking position selection and stacking sequence are automatically calculated, the calculation result is accumulated according to manual experience and data deposition, and planning personnel in charge of selecting the stacking position do not need years of work experience and professional ability, so that the enterprise cost is effectively reduced.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of an intelligent selection method for a bulk cargo wharf stock yard stacking position according to a first embodiment of the invention;
fig. 2 is a schematic diagram of an intelligent selection method for bulk cargo wharf stock yard stacking positions according to a second embodiment of the invention;
fig. 3 is a schematic diagram of an intelligent selection system for bulk cargo wharf stock yard stacking positions according to the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiment one of intelligent selection method for bulk cargo wharf stock yard stacking position
As shown in fig. 1, an intelligent selection method of a yard position comprises the following steps:
s1: acquiring stack selection data and preprocessing the stack selection data;
in practical application, the stack selection data comprises ship information, ship cargo information, wharf information and weather information.
In practical application, ship information comprises ship anchoring time, ship cargo handling names, ship estimated arrival berth time, ship estimated start time, estimated completion time, ship draft and the like;
ship cargo information including cargo volume information, cargo type information, cargo moisture information, cargo taste information, density information, estimated cargo delivery time, and the like of ship cargo;
the wharf information comprises the depth of a berth, the length of a stock yard from the berth, the stock cost of the stock yard, information on whether the stack positions of the stock yard are occupied or not, current and future predicted operation information of the stock yard, cargo information of each stack position of the stock yard and the like;
weather information including whether it is raining, whether it is fogging, whether it is blowing, etc.
In practical application, the wharf comprises the BDQs, the BDQs refer to the conveyor belts from the berth where the ship is docked to the stockyard berth, and each BDQ can only be used by one ship at the same time.
In practice, once the BDQ is used by one vessel, the corresponding area on the conveyor belt is not available for other vessels until the vessel's cargo is completely transferred. It is therefore necessary to assess before use whether a BDQ is to be allocated to the vessel for use, this being the stacking sequence, which is good enough to avoid the conflicting times of the conveyors and better use the stacking position of the yard.
In practical application, the pre-processing of the stack selection data specifically comprises the following steps: defining parameter values according to the stack selection data; and evaluating the matching score of the cargo and the stacking position according to the ship information, the ship cargo information, the wharf information, the weather information and the weight given by the manpower or the system.
In practical applications, the defined parameter values include the ship cargo quantity, the ship quantity, the stack cargo quantity and the like.
In practice, the defined parameter values and the calculated match scores are used in a stacking selection assessment function.
S2: constructing a stack position selection evaluation function according to the preprocessed stack selection data, and solving to obtain a stack selection result;
in practical applications, the berth selection evaluation function is as follows:
Figure BDA0002713012350000061
wherein the parameters include: whether the ith ship selects the jth stacking position a ij E, e.g. 0,1, selecting a value of 1, and selecting a value of 0 without selecting;
the amount z of cargo to be distributed by the kth ship on the 1 st track kl ≥0；
The amount yard of goods that can be used in the s-th stack position s ；
The number n of ships;
match Score for ith ship at jth buttress position ij ；
Cargo quantity SizeNeed required for ith ship i ；
The number m of the stack positions;
the number r of BDQs;
in practical application, the above parameters are all defined in the parameter evaluation of the stack selection data in step S1.
Meanwhile, the stacking position conditions to be met are as follows:
Figure BDA0002713012350000062
Figure BDA0002713012350000063
Figure BDA0002713012350000064
Figure BDA0002713012350000065
Figure BDA0002713012350000066
the significance lies in that: the number of the stacking positions is q, and the condition 1 is that each stacking position is only allocated to one ship; condition 2 is that the number of berths each ship can assign cannot exceed w; condition 3 is that the amount of cargo held in the pile space allocated to each ship is equal to or greater than the required amount of cargo; condition 4 is the allocation of the first BDQ for the ith ship, penalizing if the recommended cargo amount given is exceeded; condition 5 is that the s BDQ usage time of the i-th ship is equal to or less than the available time.
In practice, the meaning of the above function is the highest score in the case where each BDQ is assigned its desired quality and the quality that needs to be assigned cannot be too far from the desired quality.
In practical application, the method combining the branch definition method and the cutting plane method is adopted to solve the stacking position selection evaluation function, and a which enables the value of the stacking position selection evaluation function to be highest and meets the stacking position condition is solved ij Of value, i.e. specific ship berthsSelecting the result
In practical application, the method of combining the branch definition method and the secant plane method specifically comprises the following steps:
scheme 1 (using the branch definition method) comprises the following steps:
s (a) 1, the original problem is rewritten into a standard type of (mixed integer) linear programming problem. And initializing an optimal solution, and solving the corresponding solution of linear programming without considering integer limit to obtain the upper bound and the lower bound of the branch definition method.
S (a) 2, if the result is an integer solution, ending the discussion, wherein the integer solution is the optimal solution required by us. If the solution is a non-integer solution, the original problem is branched, and the upper and lower bounds of the corresponding branch are obtained by adopting a linear relaxation method.
And S (a) 3, judging whether the new branch meets the conditions, if not, pruning, if the upper bound and the lower bound obtained by the branch are not higher than the upper bound and the lower bound of the previous step under the met conditions, pruning the branch, otherwise, not pruning.
And S (a) 4, traversing all variables in the S (a) 3 until all branches and leaves are cut.
Scheme 2 (cut plane method) comprises the following steps:
s (b) 1, the original problem is rewritten into a standard type of a (mixed integer) linear programming problem. The relaxation variables are increased and an initial simplex table and an optimal simplex table of (LP) are obtained. And initializing an optimal solution, and solving a corresponding solution of the linear programming without considering integer limit.
S (b) 2, if the result is an integer solution, ending the discussion, wherein the integer solution is the optimal solution required by us. If the non-integer solution is adopted, a cutting plane is introduced, a component which is not an integer is selected, the coefficient integer and the decimal of the row in the optimal simple form table are decomposed, and the row is taken as a source row of the row to be used as a cutting plane equation.
And S (b) 3, placing the obtained secant plane equation as a new constraint condition in an optimal simplex table (adding a single column vector at the same time), and solving a new optimal solution by using a dual simplex method in the same way as the S (b) 1.
In practical application, the two solutions S (a) and S (b) can be simultaneously calculated in parallel without mutual interference, and the calculation rate is greatly improved.
In practical application, the stacking position selection evaluation function is solved as a ij If a has a value of ij A value of 1 indicates that the ith ship selects the jth stacking position, if a ij The value of (1) is 0, namely the ith ship does not select the jth stacking position, so that a specific stacking position selection scheme of the ship is solved, a feasible solution is preliminarily given, and the possibility of the sort of the stacking sequence is greatly reduced.
In practical application, the solved a ij And the feasible solution is a feasible ship stacking selection scheme, and the feasible stacking selection schemes are traversed in the next step to obtain a specific stacking sequence.
S3: constructing a stack order evaluation function according to the stack selection result, and solving to obtain a stack order;
in practice, the stacking sequence is specified as when the ship is going to work to which position.
In practical applications, the stacking order evaluation function is:
Figure BDA0002713012350000081
Figure BDA0002713012350000082
Figure BDA0002713012350000083
Figure BDA0002713012350000084
Figure BDA0002713012350000085
y ij ≥M*y i1 j＝13，…，18
Figure BDA0002713012350000086
Figure BDA0002713012350000087
wherein the parameters include: recommended cargo quantity BDQccupy given by jth BDQ of ith ship under condition of average residual mass ij ；
The jth BDQ available time BDQtime of the ith ship ij ；
Arrival time T of ith ship istart ；
Departure time T of ith ship istart ；
Cargo quantity m of ith ship i ；
Stacking sequence symbols:
0-1 parameter y of the ith ship ij ∈{0，1}，1≤j≤12；
Continuous variable y of ith ship ij ，13≤j≤18；
Starting variable y of ith ship ij J is more than or equal to 19 and less than or equal to 24, which means that the ith ship is supposed to have 3 BDQs available and can not be used simultaneously with each other, and the working time of the BDQ1 is [ y [) i19 ，y i20 ]BDQ2 has a working time of y i21 ，y i22 ]BDQ3 has a working time of y i23 ，y i24 ]。
In practical application, after a stack position selection result is obtained, the position of each ship corresponding to the stack position is obtained, and the stacking sequence evaluation function is solved by traversing all stacking operation sequences to obtain the optimal stacking sequence result.
In practical application, the stacked sequential evaluation function is a linear programming problem, and the function solution is to solve the linear programming problem.
In practice, a result of a feasible selection of the crenels is obtained according to step S2, where it is verified whether the conditions of the linear programming problems are met. E.g., S2, results in 50 possible solutions (in optimal descending order), then at this step, for each solution, a palletising order is performed.
For example, the first solution is that the cargo of two ships selects 3 stacking positions, the first ship has 1 stacking position (a), the second ship has 2 stacking positions (b 1, b 2), and the order of (a, b1, b 2) is verified, whether it is feasible to bring the order into the linear programming condition, and then the process is finished. If the sequence of (a, b2 and b 1) is feasible, the feasible verification is finished, and the infeasible continuous verification is carried out; traversing all possible orders, if none, then find the second of 50 solutions and continue validation until a feasible solution is found.
S4: and selecting the stacking positions according to the stacking sequence.
In practical application, after an optimal stacking sequence is found, the ship performs stacking operation according to the sequence, and the optimal stacking effect can be achieved.
Second embodiment of intelligent selection method for bulk cargo wharf stock yard stacking position
As shown in fig. 2, an intelligent selection method of a yard position comprises the following steps:
s1: acquiring stack selection data and preprocessing the stack selection data;
in practical application, the stack selection data comprises ship information, ship cargo information, wharf information and weather information.
In practical application, ship information comprises ship anchoring time, ship cargo handling names, ship estimated arrival berth time, ship estimated start time, estimated completion time, ship draft and the like;
ship cargo information including cargo volume information, cargo type information, cargo moisture information, cargo taste information, density information, estimated cargo delivery time, and the like of ship cargo;
the wharf information comprises the depth of a berth, the length of a stock yard from the berth, the stock cost of the stock yard, information on whether the stack positions of the stock yard are occupied or not, current and future predicted operation information of the stock yard, cargo information of each stack position of the stock yard and the like;
weather information including whether it is raining, whether it is fogging, whether it is blowing, etc.
In practical application, the wharf comprises BDQs, the BDQs refer to conveyor belts from berths where ships are berthed to storefront berths, and each BDQ can only be used by one ship at the same time.
In practice, a BDQ is used by one ship, and the corresponding area on the conveyor belt is not available for other ships until the ship's cargo is completely transported. It is therefore necessary to assess before use whether a BDQ is to be allocated to the vessel, this being in a stacking sequence which avoids the conflicting time of the conveyor belts and better uses the stacking position of the yard.
In practical application, the preprocessing of the stack selection data specifically comprises the following steps: defining parameter values according to the stack selection data; and evaluating the matching score of the goods and the stacking position according to the ship information, the ship goods information, the wharf information, the weather information and the weight given by the manual or system.
In practical applications, the defined parameter values include the ship cargo quantity, the ship quantity, the stack cargo quantity and the like.
In practice, the defined parameter values and the calculated match scores are used in a stacking selection assessment function.
S2: constructing a stack position selection evaluation function according to the preprocessed stack selection data, and solving to obtain a stack selection result;
in practical applications, the berth selection evaluation function is as follows:
Figure BDA0002713012350000101
wherein the parameters include: whether the ith ship selects the jth stacking position a ij The duration is 1 when the element belongs to {0,1}, and the duration when the element is not selected is 0;
the amount z of cargo to be distributed by the kth ship on the 1 st track kl ≥0；
The amount yard of goods available for the s-th stack space s ；
The number n of ships;
match Score for ith ship at jth buttress position ij ；
Quantity SizeNeed of cargo required for ith ship i ；
The number m of the stack positions;
the number r of BDQs;
in practical application, the above parameters are defined or calculated in the step S1 of evaluating the stacking data parameters.
Meanwhile, the stacking position conditions to be met are as follows:
Figure BDA0002713012350000102
Figure BDA0002713012350000103
Figure BDA0002713012350000111
Figure BDA0002713012350000112
Figure BDA0002713012350000113
the significance lies in that: the number of the stacking positions is q, and the condition 1 is that each stacking position is only distributed to one ship; condition 2 is that the number of piles to which each vessel can be allocated cannot exceed w; condition 3 is that the amount of cargo held in the pile space allocated to each ship is equal to or greater than the required amount of cargo; condition 4 is the allocation of the first BDQ for the ith ship, penalizing if the recommended cargo amount given is exceeded; condition 5 is that the s BDQ lifetime of the i-th ship is less than or equal to the available time.
In practice, the meaning of the above function is the highest score in the case where each BDQ is assigned its desired quality and the quality that needs to be assigned cannot be too far from the desired quality.
In practical application, the method combining the branch definition method and the plane cutting method is adopted to solve the stacking position selection evaluation function, and a which enables the value of the stacking position selection evaluation function to be highest and meets the stacking position condition is solved ij Value of (2), i.e. specific vessel berth selection result
In practical application, the method of combining the branch definition method and the secant plane method specifically comprises the following steps:
scheme 1 (using branch definition) comprises the following steps:
s (a) 1, the original problem is rewritten into a standard type of (mixed integer) linear programming problem. And initializing an optimal solution, and solving the corresponding solution of linear programming without considering integer limit to obtain the upper bound and the lower bound of the branch definition method.
S (a) 2, if the result is an integer solution, ending the discussion, wherein the integer solution is the optimal solution to be expected. If the solution is a non-integer solution, the original problem is subjected to branch processing, and the upper and lower boundaries of the corresponding branch are obtained by adopting a linear relaxation method.
And S (a) 3, judging whether the new branch meets the condition, if not, pruning, if the upper bound and the lower bound obtained by the branch are not higher than the upper bound and the lower bound of the previous step under the met condition, pruning the branch, otherwise, not pruning.
And S (a) 4, traversing S (a) 3 for all variables until all branches and leaves are cut.
Scheme 2 (cut plane method) comprises the following steps:
s (b) 1, the original problem is rewritten into a standard type of a (mixed integer) linear programming problem. The relaxation variables are increased and an initial simplex table and an optimal simplex table of (LP) are obtained. And initializing an optimal solution, and solving a corresponding solution of the linear programming without considering integer limit.
S (b) 2, if the result is an integer solution, ending the discussion, wherein the integer solution is the optimal solution to be expected. If the non-integer solution is adopted, a cutting plane is introduced, a component which is not an integer is selected, the coefficient integer and the decimal of the row in the optimal simple form table are decomposed, and the row is taken as a source row of the row to be used as a cutting plane equation.
And S (b) 3, placing the obtained secant plane equation as a new constraint condition in the optimal simplex table (adding a single-bit column vector at the same time), and solving a new optimal solution by using a dual simplex method in the same way as the S (b) 1.
In practical application, the two solutions S (a) and S (b) can be simultaneously calculated in parallel without mutual interference, and the calculation rate is greatly improved.
In practical application, the stacking position selection evaluation function is solved as a ij If a has a value of ij A value of 1 indicates that the ith ship selects the jth stacking position, if a ij The value of (1) is 0, namely the ith ship does not select the jth stacking position, so that a specific stacking position selection scheme of the ship is solved, a feasible solution is preliminarily given, and the possibility of the sort of the stacking sequence is greatly reduced.
In practical application, the solved a ij And the feasible solution is a feasible ship stacking selection scheme, and the feasible stacking selection schemes are traversed in the next step to obtain a specific stacking sequence.
S3: constructing a stack order evaluation function according to the stack selection result, and solving to obtain a stack order;
in practice, the stacking sequence is specified as when the ship is going to work to which position.
In practical applications, the stacking order evaluation function is:
Figure BDA0002713012350000121
Figure BDA0002713012350000122
Figure BDA0002713012350000123
Figure BDA0002713012350000124
Figure BDA0002713012350000125
y ij ≥M*y i1 j＝13，…，18
Figure BDA0002713012350000126
Figure BDA0002713012350000127
wherein the parameters include: recommended cargo quantity BDQccupy given by jth BDQ of ith ship under condition of average residual mass ij ；
The jth BDQ available time BDQtime of the ith ship ij ；
Arrival time T of ith ship istart ；
Departure time T of ith ship istart ；
Cargo volume m of ith ship i ；
Stacking sequence symbols:
0-1 parameter y for the ith ship ij ∈{0，1}，1≤j≤12；
Continuous variable y of ith ship ij ，13≤j≤18；
Starting variable y of ith ship ij J is more than or equal to 19 and less than or equal to 24, which means that the ith ship is supposed to have 3 BDQs available and can not be used simultaneously, and the working time of the BDQ1 is [ y% i19 ，y i20 ]BDQ2 has a working time of y i21 ，y i22 ]BDQ3 has a working time of y i23 ，y i24 ]。
In practical application, after a stacking position selection result is obtained, the position of each ship corresponding to the stacking position is obtained, and the stacking sequence evaluation function is solved by traversing all stacking operation sequences, so that the optimal stacking sequence result is obtained.
In practical application, the stacked sequential evaluation function is a linear programming problem, and the function solution is to solve the linear programming problem.
In practice, the result of a feasible choice of the crenels is obtained according to step S2, where verification is made as to whether the conditions of the linear programming problems are met. For example, S2 results in 50 possible solutions (in optimal descending order), then at this step, for each solution, a stacking order arrangement is performed.
For example, the first solution is that the cargo of two ships selects 3 stacking positions, the first ship has 1 stacking position (a), the second ship has 2 stacking positions (b 1, b 2), and the order of (a, b1, b 2) is verified, whether it is feasible to bring the order into the linear programming condition, and then the process is finished. If the sequence of (a, b2 and b 1) is feasible, the feasible verification is finished, and the infeasible continuous verification is carried out; traversing all the possible orders, if none, then find the second of 50 solutions and continue the validation until a feasible solution is found.
S4: selecting the stack position according to the stacking sequence;
in practical application, after an optimal stacking sequence is found, the ship performs stacking operation according to the sequence, and the optimal stacking effect can be achieved.
S5: and storing the stacking sequence results in a database, and forming a data statistics module through a statistics device.
In practical application, the data statistical module is formed to facilitate the subsequent stacked sequential effect analysis.
Embodiment of intelligent selection system for bulk cargo wharf stock yard stacking position
As shown in fig. 3, an intelligent selection system for bulk cargo terminal yard position comprises:
the user module comprises a data input device and a parameter modifier, the data input device is used for inputting stack selection data, and the parameter modifier is used for adjusting data parameters;
the calculating module comprises a stacking position selector and a stacking sequencer, the stacking position selector is used for constructing a stacking position selection evaluation function to obtain a stacking selection result, and the stacking sequencer is used for constructing a stacking sequence evaluation function to obtain a stacking sequence;
and the stacking position selection module is used for selecting the stacking positions according to the stacking sequence.
In practical application, the system also comprises a data statistics module which comprises a database and a statistics device, wherein the database receives the data of the calculation module, and the statistics device carries out statistical analysis on the data.
In practical application, the user module, the calculation module and the data statistics module are connected in pairs and can transmit data mutually.
The implementation of the invention has the advantages that: the invention discloses an intelligent selection method and system for bulk cargo wharf stock yard stacking positions, wherein the method comprises the following steps: acquiring stack selection data and preprocessing the stack selection data; constructing a pile position selection evaluation function according to the preprocessed pile selection data, and solving to obtain a pile selection result; constructing a stack order evaluation function according to the stack selection result, and solving to obtain a stack order; and selecting the stacking positions according to the stacking sequence. The system comprises: a user module; a calculation module; a stack position selection module; and a data statistics module. The method has the advantages that the stacking position selection and stacking sequence are automatically calculated, the calculation result is accumulated according to manual experience and data deposition, and planning personnel in charge of selecting the stacking position do not need years of work experience and professional ability, so that the enterprise cost is effectively reduced.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention disclosed herein are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (9)

1. An intelligent selection method for bulk cargo wharf stock yard stock position is characterized by comprising the following steps:
acquiring stack selection data and preprocessing the stack selection data;
constructing a pile position selection evaluation function according to the preprocessed pile selection data, and solving to obtain a pile selection result; the stacking position selection evaluation function is as follows:
Figure FDA0003727223140000011
wherein the parameters include: whether the ith ship selects the jth stacking position a ij The duration is 1 when the element belongs to {0,1}, and the duration when the element is not selected is 0;
the amount z of cargo to be distributed by the kth ship on the 1 st track kl ≥0；
The amount yard of goods available for the s-th stack space s ；
The number n of ships;
match Score for ith ship at jth buttress position ij ；
Quantity SizeNeed of cargo required for ith ship i ；
The number m of the stack positions;
the number r of the BDQs is the conveying belt from the berth of the ship berthing to the berth of the storage yard;
constructing a stack sequence evaluation function according to the stack selection result, and solving to obtain a stack sequence;
Figure FDA0003727223140000012
Figure FDA0003727223140000013
Figure FDA0003727223140000014
Figure FDA0003727223140000015
Figure FDA0003727223140000016
y ij ≥M*y i1 j＝13,…,18
Figure FDA0003727223140000017
Figure FDA0003727223140000018
wherein the parameters include: recommended cargo quantity BDQccupy given by jth BDQ of ith ship under condition of average residual mass ij ；
The jth BDQ available time BDQtime of the ith ship ij ；
Arrival time T of ith ship istart ；
Departure time T of ith ship istart ；
Cargo volume m of ith ship i ；
Stacking sequential symbols:
0-1 parameter y for the ith ship ij ∈{0,1},1≤j≤12；
Continuous variable y of ith ship ij ,13≤j≤18；
Starting variable y of ith ship ij J is more than or equal to 19 and less than or equal to 24, which means that the ith ship is supposed to have 3 BDQs available and can not be used simultaneously with each other, and the working time of the BDQ1 is [ y [) i19 ,y i20 ]BDQ2 has a working time of y i21 ,y i22 ]BDQ3 has a working time of y i23 ,y i24 ]；
And selecting the stacking positions according to the stacking sequence.
2. The intelligent selection method of bulk cargo terminal yard berths according to claim 1, characterized in that the pile selection data comprises ship information, ship cargo information, terminal information and weather information.
3. The intelligent selection method for the bulk cargo terminal yard pile position according to claim 2, wherein the pile selection data is preprocessed specifically as follows: defining parameter values according to the stack selection data; and evaluating the matching score of the goods and the stacking position according to the ship information, the ship goods information, the wharf information, the weather information and the weight given by the manual or system.
4. The intelligent selection method for the bulk terminal yard position according to claim 1, wherein the terminal comprises a BDQ, the BDQ is a conveyor belt from the berth where the ship is berthed to the yard position, and each BDQ can only be used by one ship at the same time.
5. The intelligent selection method for the bulk cargo terminal yard position according to claim 1, wherein the position condition to be satisfied by the position selection evaluation function is:
Figure FDA0003727223140000021
Figure FDA0003727223140000022
Figure FDA0003727223140000023
Figure FDA0003727223140000024
Figure FDA0003727223140000025
the significance lies in that: the number of the stacking positions is q, and the condition 1 is that each stacking position is only distributed to one ship; condition 2 is that the number of piles to which each vessel can be allocated cannot exceed w; condition 3 is that the amount of cargo held in the pile space allocated to each ship is equal to or greater than the required amount of cargo; condition 4 is the allocation of the first BDQ for the ith ship, penalizing if the recommended cargo amount given is exceeded; condition 5 is that the s BDQ usage time of the i-th ship is equal to or less than the available time.
6. The intelligent selection method for the bulk cargo wharf yard stacking position according to claim 5, characterized in that the method combining the branch definition method and the cut plane method is adopted to solve the stacking position selection evaluation function, and all a that enable the value of the stacking position selection evaluation function to be highest and meet the stacking position condition are solved ij I.e. the result of the selection of a particular ship.
7. The intelligent selection method for the bulk cargo wharf yard stacking position according to claim 1, wherein after the stacking result is obtained, the position of the stacking position corresponding to each ship is obtained, and the stacking sequence evaluation function is solved by traversing all stacking operation sequences to obtain the optimal stacking sequence.
8. The intelligent selection method of bulk terminal stacking positions according to one of claims 1 to 7, further comprising the steps of: and storing the stacking sequence results in a database, and forming a data statistics module through a statistics device.
9. An intelligent selection system of bulk terminal stacking positions, characterized in that the intelligent selection system of the stacking positions is used for executing the intelligent selection method of the bulk terminal stacking positions of claim 1, and comprises the following steps:
the user module comprises a data input device and a parameter modifier, wherein the data input device is used for inputting stack selection data, and the parameter modifier is used for adjusting data parameters;
the calculating module comprises a stacking position selector and a stacking sequencer, wherein the stacking position selector is constructed to enable a stacking position selection evaluation function with the highest score to obtain a stacking selection result under the condition that each BDQ is allocated with ideal quality and the quality needing to be allocated cannot be far away from the required quality, and the stacking sequencer is constructed to obtain a stacking sequence based on a stacking sequence evaluation function of a linear programming problem;
and the stacking position selection module is used for selecting the stacking positions according to the stacking sequence.
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