CN116108550B - BIM-based dynamic optimization method and system for multi-mode intermodal - Google Patents

BIM-based dynamic optimization method and system for multi-mode intermodal Download PDF

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CN116108550B
CN116108550B CN202310392412.3A CN202310392412A CN116108550B CN 116108550 B CN116108550 B CN 116108550B CN 202310392412 A CN202310392412 A CN 202310392412A CN 116108550 B CN116108550 B CN 116108550B
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park
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周明翔
程思宇
张琨
罗小华
赵迪
光振雄
董云松
雷崇
殷勤
邱绍峰
李加祺
刘辉
张俊岭
彭方进
李成洋
朱冬
李晓聃
应颖
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China Railway Siyuan Survey and Design Group Co Ltd
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Abstract

The invention discloses a dynamic optimization method and a system for multi-mode intermodal based on BIM, wherein the method comprises the following steps: acquiring equipment information of freight mechanical equipment, and modeling the freight mechanical equipment through BIM to generate a freight mechanical equipment model; acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein the material properties, physical characteristics and constraint conditions of the freight park model are set; BIM simulation of the whole process of arriving at the container and sending the container is carried out according to the freight mechanical equipment model and the freight park model, time T required by transportation of multi-mode intermodal is generated, the fatigue limit times of the freight mechanical equipment are obtained according to the material properties of the freight mechanical equipment model, and the maintenance time required by the freight mechanical equipment is calculated according to the fatigue limit times; according to the modeling of the freight mechanical equipment and the freight park model, the optimal transportation route in the freight park is calculated by combining with an ant colony algorithm, a new heuristic function is set, and the ant colony algorithm is adjusted.

Description

BIM-based dynamic optimization method and system for multi-mode intermodal
Technical Field
The invention belongs to the technical field of BIM-based multi-connected transportation simulation, and particularly relates to a BIM-based dynamic optimization method and system for multi-connected transportation.
Background
The multi-type intermodal transportation is late in starting in China, relates to the connection and integration of various transportation modes and the management coordination among multiple departments, and has the situations of opaque information resources, incomplete resource utilization, insufficient connection among all processes and no maximum transport capacity of the multi-type intermodal transportation. Most of the conventional management of multi-mode intermodal is still in a bar management mode, namely carriers with different transportation modes are only responsible for the management work of a certain section of transportation in the multi-mode intermodal process, so that the conventional multi-mode intermodal project generally lacks a regulation mode for the whole period of the project, and as the multi-mode intermodal generally relates to at least two transportation modes, once the multi-mode intermodal process flow planning is insufficient in the early stage of the project, and a great amount of manpower and material resources are consumed for regulating the scheme of the multi-mode intermodal after the project construction is completed. BIM (Building Information Modeling), by establishing a BIM model related to multi-mode intermodal, a manager can effectively observe detailed information parameters of each link, calculate problems existing in the items in advance through simulation, find an optimal solution and improve the working efficiency of multi-mode intermodal.
Disclosure of Invention
In order to solve the technical problems, the invention provides a dynamic optimization method of multi-mode intermodal based on BIM, which comprises the following steps:
acquiring equipment information of the freight mechanical equipment, modeling the freight mechanical equipment through BIM, and generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein the material properties, physical characteristics and constraint conditions of the freight park model are set;
according to a freight mechanical equipment model and a freight park model, BIM simulation of the whole process of arriving at a container and sending the container is carried out, time T required by transportation of multi-type intermodal transportation is generated, the fatigue limit times of the freight mechanical equipment are obtained according to the material properties of the freight mechanical equipment model, and the maintenance time required by the freight mechanical equipment is calculated according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
according to the modeling of the freight mechanical equipment and the freight park model, the optimal transportation route in the freight park is calculated by combining an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Further, the physical features of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit movement mileage and maximum rotation angle of the freight mechanical equipment;
the physical features of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
Further, calculating the maintenance time required for the freight machine includes:
Figure SMS_1
；
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_2
is a safety factor.
Further, setting a new heuristic function includes: road traffic index
Figure SMS_3
And the road passing difficulty coefficient
Figure SMS_4
And calculating the equivalent length of the container transportation path +.>
Figure SMS_5
According to equivalent length->
Figure SMS_6
Setting a new heuristic function ++>
Figure SMS_7
。
Further, according to the equivalent length
Figure SMS_8
Setting a new heuristic function includes:
calculating road traffic index
Figure SMS_9
；
Figure SMS_10
，
t is the time for the ant to move from node i to node j,
Figure SMS_11
for the road visibility influence coefficient from node i to node j, +.>
Figure SMS_12
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure SMS_13
，
Figure SMS_14
；
Figure SMS_15
For the current speed of a truck transporting containers in a freight park +.>
Figure SMS_16
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure SMS_17
，
Figure SMS_18
，
Figure SMS_19
Is the geometric length of the channel in the freight park;
heuristic function
Figure SMS_20
，
Figure SMS_21
，
Equivalent length of
Figure SMS_22
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
Further, setting a new heuristic function includes:
Figure SMS_23
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_24
for heuristic function ++>
Figure SMS_25
Is a weight coefficient>
Figure SMS_26
Distance from current node to target node, road traffic index->
Figure SMS_27
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure SMS_28
The value range of (2) is [0,1 ]]。
The invention also provides a dynamic optimization system of the multi-mode intermodal based on BIM, which comprises the following steps:
the equipment information acquisition module is used for acquiring equipment information of the freight mechanical equipment, modeling the freight mechanical equipment through BIM, generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
the system comprises a park information acquisition module, a freight park information generation module and a freight park information generation module, wherein the park information acquisition module is used for acquiring park information of a freight park, modeling the freight park through BIM and generating a freight park model, and setting material properties, physical characteristics and constraint conditions of the freight park model;
the simulation module is used for carrying out BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
and the optimal transportation route calculation module is used for calculating an optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model and combining with an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Further, the physical features of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit movement mileage and maximum rotation angle of the freight mechanical equipment;
the physical features of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
Further, calculating the maintenance time required for the freight machine includes:
Figure SMS_29
，
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_30
is a safety factor.
Further, setting a new heuristic function includes: road traffic index
Figure SMS_31
And the road passing difficulty coefficient
Figure SMS_32
And calculating the equivalent length of the container transportation path +.>
Figure SMS_33
According to equivalent length->
Figure SMS_34
Setting a new heuristic function ++>
Figure SMS_35
。
In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:
the BIM technology is integrated into the process flow design optimization, the park construction optimization and the operation maintenance optimization of the multi-mode intermodal transportation, the multi-mode intermodal transportation process route, the park construction scheme and the later operation maintenance can be optimized at the beginning of the design, meanwhile, the multi-mode intermodal transportation park transportation path can be optimized through the ant colony algorithm, the advantages of the multi-mode intermodal transportation in the cargo transportation can be fully exerted, and the rapid development of the multi-mode intermodal transportation industry in China can be assisted.
Drawings
FIG. 1 is a flow chart of the method of embodiment 1 of the present invention;
fig. 2 is a block diagram of a system of embodiment 2 of the present invention.
Detailed Description
In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments.
The method provided by the invention can be implemented in a terminal environment, wherein the terminal can comprise one or more of the following components: processor, storage medium, and display screen. Wherein the storage medium has stored therein at least one instruction that is loaded and executed by the processor to implement the method described in the embodiments below.
The processor may include one or more processing cores. The processor connects various parts within the overall terminal using various interfaces and lines, performs various functions of the terminal and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the storage medium, and invoking data stored in the storage medium.
The storage medium may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (ROM). The storage medium may be used to store instructions, programs, code sets, or instructions.
The display screen is used for displaying a user interface of each application program.
In addition, it will be appreciated by those skilled in the art that the structure of the terminal described above is not limiting and that the terminal may include more or fewer components, or may combine certain components, or a different arrangement of components. For example, the terminal further includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and the like, which are not described herein.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a dynamic optimization method for multi-modal intermodal based on BIM, including:
step 101, acquiring equipment information of freight mechanical equipment, modeling the freight mechanical equipment through BIM, and generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
specifically, the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit range and maximum rotation angle of the freight machine.
Step 102, acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein material properties, physical characteristics and constraint conditions of the freight park model are set;
specifically, the physical characteristics of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
Step 103, performing BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
specifically, calculating the maintenance time required for the freight machine includes:
Figure SMS_36
，
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_37
is a safety factor.
Thus, the maintenance time of a cargo facility such as a crane is:
Figure SMS_38
；
thus, the maintenance time for the discharge device, such as a dump platform, is:
Figure SMS_39
；
thus, the repair and maintenance time for the transport device, such as the header card, is:
Figure SMS_40
；
Figure SMS_41
-loading time; />
Figure SMS_42
-discharge time; />
Figure SMS_43
-transport time, by grasping the maintenance time of the equipment to invoke the transport engagement of the alternative equipment model in time, guaranteeing the continuity of transport.
And 104, calculating the optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model by combining an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Specifically, according to the ant colony algorithm, the probability that the ant moves from the point i to the point j according to the pseudo-random proportion rule is as follows:
Figure SMS_44
，
wherein the method comprises the steps of
Figure SMS_45
For information heuristic factors, the larger the value, the larger the probability of ant selection; />
Figure SMS_46
The influence degree of the heuristic information on the ant path in the motion process of the ants is reflected as a desired heuristic factor; />
Figure SMS_47
Representing the expected degree of ants from i to j as a heuristic function; />
Figure SMS_48
Represents a set of nodes that can be reached directly from node i to node j, but not accessed by ants, < ->
Figure SMS_49
Representing the pheromone amount.
Specifically, setting a new heuristic function includes: road traffic index
Figure SMS_50
And the road passing difficulty coefficient
Figure SMS_51
And calculating the equivalent length of the container transportation path +.>
Figure SMS_52
According to equivalent length->
Figure SMS_53
Setting a new heuristic function ++>
Figure SMS_54
。
Specifically, according to equivalent length
Figure SMS_55
Setting a new heuristic function includes:
calculating road traffic index
Figure SMS_56
，
Figure SMS_57
，
t is the time for the ant to move from node i to node j,
Figure SMS_58
for the road visibility influence coefficient from node i to node j, +.>
Figure SMS_59
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure SMS_60
，
Figure SMS_61
，
Figure SMS_62
For the current speed of a truck transporting containers in a freight park +.>
Figure SMS_63
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure SMS_64
，
Figure SMS_65
，
Figure SMS_66
Is the geometric length of the channel in the freight park;
heuristic function
Figure SMS_67
，
Figure SMS_68
，
Equivalent length of
Figure SMS_69
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
Specifically, setting a new heuristic function may also be:
Figure SMS_70
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_71
for heuristic function ++>
Figure SMS_72
Is a weight coefficient>
Figure SMS_73
For the distance of the current node to the target node, road traffic index +.>
Figure SMS_74
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure SMS_75
The value range of (2) is [0,1 ]]。
Example 2
As shown in fig. 2, the embodiment of the present invention further provides a dynamic optimization system for multi-modal intermodal based on BIM, including:
the equipment information acquisition module is used for acquiring equipment information of the freight mechanical equipment, modeling the freight mechanical equipment through BIM, generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
specifically, the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit range and maximum rotation angle of the freight machine.
The system comprises a park information acquisition module, a freight park information generation module and a freight park information generation module, wherein the park information acquisition module is used for acquiring park information of a freight park, modeling the freight park through BIM and generating a freight park model, and setting material properties, physical characteristics and constraint conditions of the freight park model;
specifically, the physical characteristics of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
The simulation module is used for carrying out BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
specifically, calculating the maintenance time required for the freight machine includes:
Figure SMS_76
，
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_77
is a safety factor.
Thus, the maintenance time of a cargo facility such as a crane is:
Figure SMS_78
；
thus, the maintenance time for the discharge device, such as a dump platform, is:
Figure SMS_79
；
thus, the repair and maintenance time for the transport device, such as the header card, is:
Figure SMS_80
；
Figure SMS_81
-loading time; />
Figure SMS_82
-discharge time; />
Figure SMS_83
-transport time, by grasping the maintenance time of the equipment to invoke the transport engagement of the alternative equipment model in time, guaranteeing the continuity of transport.
And the optimal transportation route calculation module is used for calculating an optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model and combining with an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Specifically, according to the ant colony algorithm, the probability that the ant moves from the point i to the point j according to the pseudo-random proportion rule is as follows:
Figure SMS_84
，
wherein the method comprises the steps of
Figure SMS_85
For information heuristic factors, the larger the value, the larger the probability of ant selection; />
Figure SMS_86
The influence degree of the heuristic information on the ant path in the motion process of the ants is reflected as a desired heuristic factor; />
Figure SMS_87
Representing the expected degree of ants from i to j as a heuristic function; />
Figure SMS_88
Representing the set of nodes that can be reached directly from node i to node j, but not accessed by ants,
Figure SMS_89
representing the pheromone amount.
Specifically, setting a new heuristic function includes: road traffic index
Figure SMS_90
And the road passing difficulty coefficient
Figure SMS_91
And calculating the equivalent length of the container transportation path +.>
Figure SMS_92
According to equivalent length->
Figure SMS_93
Setting a new heuristic function ++>
Figure SMS_94
。
Specifically, according to equivalent length
Figure SMS_95
Setting a new heuristic function includes:
calculating road traffic index
Figure SMS_96
，
Figure SMS_97
，
t is the time for the ant to move from node i to node j,
Figure SMS_98
for the road visibility influence coefficient from node i to node j, +.>
Figure SMS_99
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure SMS_100
，
Figure SMS_101
，
Figure SMS_102
For the current speed of a truck transporting containers in a freight park +.>
Figure SMS_103
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure SMS_104
，
Figure SMS_105
，
Figure SMS_106
Is the geometric length of the channel in the freight park;
heuristic function
Figure SMS_107
，
Figure SMS_108
，
Equivalent length of
Figure SMS_109
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
Specifically, setting a new heuristic function may also be:
Figure SMS_110
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_111
for heuristic function ++>
Figure SMS_112
Is a weight coefficient>
Figure SMS_113
For the distance of the current node to the target node, road traffic index +.>
Figure SMS_114
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure SMS_115
The value range of (2) is [0,1 ]]。
Example 3
The embodiment of the invention also provides a storage medium which stores a plurality of instructions for realizing the BIM-based multi-mode intermodal dynamic optimization method.
Alternatively, in this embodiment, the storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.
Alternatively, in the present embodiment, the storage medium is configured to store program code for performing the steps of: step 101, acquiring equipment information of freight mechanical equipment, modeling the freight mechanical equipment through BIM, and generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
specifically, the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit range and maximum rotation angle of the freight machine.
Step 102, acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein material properties, physical characteristics and constraint conditions of the freight park model are set;
specifically, the physical characteristics of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
Step 103, performing BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
specifically, calculating the maintenance time required for the freight machine includes:
Figure SMS_116
，
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_117
is a safety factor.
Thus, the maintenance time of a cargo facility such as a crane is:
Figure SMS_118
；
thus, the maintenance time for the discharge device, such as a dump platform, is:
Figure SMS_119
；
thus, the repair and maintenance time for the transport device, such as the header card, is:
Figure SMS_120
；
Figure SMS_121
-loading time; />
Figure SMS_122
-discharge time; />
Figure SMS_123
-transport time, by grasping the maintenance time of the equipment to invoke the transport engagement of the alternative equipment model in time, guaranteeing the continuity of transport.
And 104, calculating the optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model by combining an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Specifically, according to the ant colony algorithm, the probability that the ant moves from the point i to the point j according to the pseudo-random proportion rule is as follows:
Figure SMS_124
，
wherein the method comprises the steps of
Figure SMS_125
For information heuristic factors, the larger the value, the larger the probability of ant selection; />
Figure SMS_126
The influence degree of the heuristic information on the ant path in the motion process of the ants is reflected as a desired heuristic factor; />
Figure SMS_127
Representing the expected degree of ants from i to j as a heuristic function; />
Figure SMS_128
Represents a set of nodes that can be reached directly from node i to node j, but not accessed by ants, < ->
Figure SMS_129
Representing the pheromone amount.
Specifically, setting a new heuristic function includes: road traffic index
Figure SMS_130
And the road passing difficulty coefficient
Figure SMS_131
And calculating the equivalent length of the container transportation path +.>
Figure SMS_132
According to equivalent length->
Figure SMS_133
Setting a new heuristic function ++>
Figure SMS_134
。
Specifically, according to equivalent length
Figure SMS_135
Setting a new heuristic function includes:
calculating road traffic index
Figure SMS_136
，
Figure SMS_137
，
t is the time for the ant to move from node i to node j,
Figure SMS_138
for the road visibility influence coefficient from node i to node j, +.>
Figure SMS_139
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure SMS_140
，
Figure SMS_141
，
Figure SMS_142
For the current speed of a truck transporting containers in a freight park +.>
Figure SMS_143
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure SMS_144
，
Figure SMS_145
，
Figure SMS_146
Is the geometric length of the channel in the freight park;
heuristic function
Figure SMS_147
，
Figure SMS_148
，
Equivalent length of
Figure SMS_149
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
Specifically, setting a new heuristic function may also be:
Figure SMS_150
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_151
for heuristic function ++>
Figure SMS_152
Is a weight coefficient>
Figure SMS_153
For the distance of the current node to the target node, road traffic index +.>
Figure SMS_154
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure SMS_155
The value range of (2) is [0,1 ]]。
Example 4
The embodiment of the invention also provides electronic equipment, which comprises a processor and a storage medium connected with the processor, wherein the storage medium stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the BIM-based multi-mode intermodal dynamic optimization method.
Specifically, the electronic device of the present embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.
The storage medium may be used to store a software program and a module, for example, a dynamic optimization method based on BIM multi-mode intermodal in the embodiment of the invention, and the processor executes various functional applications and data processing by running the software program and the module stored in the storage medium, namely, implements the dynamic optimization method based on BIM multi-mode intermodal. The storage medium may include a high-speed random access storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage medium. In some examples, the storage medium may further include a storage medium remotely located with respect to the processor, and the remote storage medium may be connected to the terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The processor may invoke the information stored in the storage medium and the application program via the transmission system to perform the following steps: step 101, acquiring equipment information of freight mechanical equipment, modeling the freight mechanical equipment through BIM, and generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
specifically, the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit range and maximum rotation angle of the freight machine.
Step 102, acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein material properties, physical characteristics and constraint conditions of the freight park model are set;
specifically, the physical characteristics of the freight park model include: the area, elevation and location of the production house, and the constraints of the freight park model include site red lines and building height limits.
Step 103, performing BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
specifically, calculating the maintenance time required for the freight machine includes:
Figure SMS_156
，
wherein: t is the running time of the freight mechanical equipment, N is the fatigue limit times of the freight mechanical equipment under the material property,
Figure SMS_157
is a safety factor.
Thus, the maintenance time of a cargo facility such as a crane is:
Figure SMS_158
；
thus, the maintenance time for the discharge device, such as a dump platform, is:
Figure SMS_159
；
thus, the repair and maintenance time for the transport device, such as the header card, is:
Figure SMS_160
；
Figure SMS_161
-loading time; />
Figure SMS_162
-discharge time; />
Figure SMS_163
-transport time, by grasping the maintenance time of the equipment to invoke the transport engagement of the alternative equipment model in time, guaranteeing the continuity of transport.
And 104, calculating the optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model by combining an ant colony algorithm, wherein a new heuristic function is set, and the ant colony algorithm is adjusted.
Specifically, according to the ant colony algorithm, the probability that the ant moves from the point i to the point j according to the pseudo-random proportion rule is as follows:
Figure SMS_164
，
wherein the method comprises the steps of
Figure SMS_165
For information heuristic factors, the larger the value, the larger the probability of ant selection; />
Figure SMS_166
The influence degree of the heuristic information on the ant path in the motion process of the ants is reflected as a desired heuristic factor; />
Figure SMS_167
Representing the expected degree of ants from i to j as a heuristic function; />
Figure SMS_168
Represents a set of nodes that can be reached directly from node i to node j, but not accessed by ants, < ->
Figure SMS_169
Representing the pheromone amount.
Specifically, setting a new heuristic function includes: road traffic index
Figure SMS_170
And the road passing difficulty coefficient
Figure SMS_171
And calculating the equivalent length of the container transportation path +.>
Figure SMS_172
According to equivalent length->
Figure SMS_173
Setting a new heuristic function ++>
Figure SMS_174
。
Specifically, according to equivalent length
Figure SMS_175
Setting a new heuristic function includes:
calculating road traffic index
Figure SMS_176
，
Figure SMS_177
，
t is the time for the ant to move from node i to node j,
Figure SMS_178
for the road visibility influence coefficient from node i to node j, +.>
Figure SMS_179
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure SMS_180
，
Figure SMS_181
，
Figure SMS_182
For the current speed of a truck transporting containers in a freight park +.>
Figure SMS_183
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure SMS_184
，
Figure SMS_185
，
Figure SMS_186
Is the geometric length of the channel in the freight park;
heuristic function
Figure SMS_187
，
Figure SMS_188
，
Equivalent length of
Figure SMS_189
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
Specifically, setting a new heuristic function may also be:
Figure SMS_190
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure SMS_191
for heuristic function ++>
Figure SMS_192
Is a weight coefficient>
Figure SMS_193
For the distance of the current node to the target node, road traffic index +.>
Figure SMS_194
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure SMS_195
The value range of (2) is [0,1 ]]。
Example 5
The embodiment also provides an ant colony algorithm based on BIM, which realizes path optimization of the multi-mode intermodal transportation park, and comprises the following specific steps:
firstly, dividing a spatial structure of a park, and establishing a grid map composed of a node set N and a channel set A, wherein N represents a set of all nodes in the process of planning a multi-type intermodal route; channel set a is the geometric length of the path between the connecting nodes. Park space information is abstracted into a network model of M (N, A) composed of node geometry N and evacuation channel geometry A, wherein N= (N) 1 ,N 2 ,… ,N n ). White nodes are represented as normal nodes and black nodes are represented as obstacle nodes, such as a multi-modal arrangement point location in a campus, a non-destination job site, etc.
Each node information further comprises static information and dynamic information, wherein the static information is defined as coordinate information N (x, y) of a node in a two-dimensional space (taking a small left corner as an origin of coordinates) in a grid, the dynamic information is expressed as N (t, R), t is a time node, and R is the number of cards in the current node.
Channel set a= (a 11 ,A 12 ,```,A mn ) Wherein A is ij Representing a passable path from node i to node j, the static information of the path is defined as a (L ij ，G ij ），L ij Representing the geometric distance length of the channel, G ij Representing a traffic barrier coefficient on the channel during actual operation; the dynamic information of the channel is defined as a (t, R ij ，K ij ) Wherein R is ij Representing the influence coefficient K of the quantity of the transport vehicles on the channel at the moment t ij And representing the T moment and the road visibility influence coefficient.
In the ant colony algorithm, ants can select paths with stronger pheromones, but if all ants select paths with stronger pheromones, the algorithm falls into local optimum, the problem of local convergence can be prevented by adjusting the pheromones of the paths, and an ant colony algorithm pheromone updating formula is as follows:
Figure SMS_196
，
Figure SMS_197
，
wherein the method comprises the steps of
Figure SMS_198
Is a pheromone volatile factor->
Figure SMS_199
For t time->
Figure SMS_200
Pheromone concentration of (2); />
Figure SMS_201
Representing the increment of pheromone on its channel; />
Figure SMS_202
An optimal evaluation value of the table path; due to->
Figure SMS_203
The value determines the searching capability and the convergence rate of the ant colony algorithm, so the patent adopts dynamic adjustment +.>
Figure SMS_204
Values to improve the pheromone update strategy are as follows:
Figure SMS_205
，
after the optimal path is calculated, if the result has no obvious change after N iterations, the method reduces
Figure SMS_206
Values to increase the global search capability of the algorithm while setting +.>
Figure SMS_207
The minimum value range of the values is used for avoiding slow convergence speed caused by too low pheromone volatilization factors. The algorithm flow is as follows:
1) Initializing a grid environment of a park, establishing a map matrix, defining an initial node and an obstacle node, and initializing dynamic information and static information of the node and the channel;
2) Initializing variables such as the maximum iteration times of the algorithm, the number of vehicles, expected heuristic factors, pheromone volatilization factors, tabu tables and the like;
3) Calculating the equivalent length between nodes;
4) Judging the condition of the pre-selected node, judging whether the node is an obstacle or not, if not, carrying out the next step, if so, returning to the third step;
5) Searching the next node to be selected through a pseudo-random proportion rule, and putting in and updating a tabu table;
6) Judging whether the selected node is a destination, stopping if the selected node is found, and recording the route and the length selected in the iteration; if not, the flow goes to a third step;
7) The global pheromone is updated. Updating the concentration of the pheromone on each transportation path, and carrying out self-adaptive adjustment on the concentration of the pheromone in the algorithm;
8) Outputting the optimal path. Judging whether the maximum iteration times are met, and if the maximum iteration times are reached, outputting an optimal path planning chart; otherwise, the flow goes to the fourth step.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed technology may be implemented in other manners. The system embodiments described above are merely exemplary, and for example, the division of the units is merely a logic function division, and there may be another division manner in actual implementation, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or partly in the form of a software product or all or part of the technical solution, which is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, randomAccess Memory), a removable hard disk, a magnetic disk, or an optical disk, or the like, which can store program codes.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.

Claims (5)

1. A method for dynamic optimization of multiple intermodal based on BIM, comprising:
acquiring equipment information of the freight mechanical equipment, modeling the freight mechanical equipment through BIM, and generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
wherein the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit movement mileage and maximum rotation angle of the freight mechanical equipment;
the physical features of the freight park model include: the area, elevation and position of the production house, and the constraint conditions of the freight park model comprise site red lines and building height limits;
acquiring park information of a freight park, modeling the freight park through BIM, and generating a freight park model, wherein the material properties, physical characteristics and constraint conditions of the freight park model are set;
according to a freight mechanical equipment model and a freight park model, BIM simulation of the whole process of arriving at a container and sending the container is carried out, time T required by transportation of multi-type intermodal transportation is generated, the fatigue limit times of the freight mechanical equipment are obtained according to the material properties of the freight mechanical equipment model, and the maintenance time required by the freight mechanical equipment is calculated according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
calculating an optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model and combining an ant colony algorithm, wherein a new heuristic function is set, the ant colony algorithm is adjusted,
wherein setting a new heuristic function comprises: road traffic index
Figure QLYQS_1
And the traffic difficulty coefficient of the road->
Figure QLYQS_2
And calculating the equivalent length of the container transportation path +.>
Figure QLYQS_3
According to equivalent length->
Figure QLYQS_4
Setting a new heuristic function
Figure QLYQS_5
；
According to equivalent length
Figure QLYQS_6
Setting a new heuristic function includes:
calculating road traffic index
Figure QLYQS_7
，
Figure QLYQS_8
，
t is the time for the ant to move from node i to node j,
Figure QLYQS_9
for the road visibility influence coefficient from node i to node j, +.>
Figure QLYQS_10
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure QLYQS_11
，
Figure QLYQS_12
，
Figure QLYQS_13
For the current speed of a truck transporting containers in a freight park +.>
Figure QLYQS_14
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure QLYQS_15
，
Figure QLYQS_16
，
Figure QLYQS_17
Is the geometric length of the channel in the freight park;
heuristic function
Figure QLYQS_18
，
Figure QLYQS_19
，
Equivalent length of
Figure QLYQS_20
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
2. The method of dynamic optimization of BIM-based multi-modal intermodal as set forth in claim 1, wherein calculating the maintenance time required for the cargo machinery includes:
Figure QLYQS_21
，
wherein:
Figure QLYQS_22
for the operating time of the freight-machine, N is the number of fatigue limits of the freight-machine in the material properties, +.>
Figure QLYQS_23
Is a safety factor.
3. The method of dynamic optimization of BIM-based multi-modal intermodal as set forth in claim 1, wherein setting the new heuristic function includes:
Figure QLYQS_24
，
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure QLYQS_25
for heuristic function ++>
Figure QLYQS_26
Is a weight coefficient>
Figure QLYQS_27
For the distance of the current node to the target node, road traffic index +.>
Figure QLYQS_28
The value range of (2) is [0,1 ]]Road traffic difficulty coefficient->
Figure QLYQS_29
The value range of (2) is [0,1 ]]。
4. A dynamic optimization system for BIM-based multi-modal intermodal, comprising:
the equipment information acquisition module is used for acquiring equipment information of the freight mechanical equipment, modeling the freight mechanical equipment through BIM, generating a freight mechanical equipment model, wherein the model precision of the freight mechanical equipment model is a component level, and setting material properties, physical characteristics and constraint conditions of the freight mechanical equipment model;
wherein the physical characteristics of the cargo machinery model include: the speed, acceleration, point location and working range of the freight machinery equipment, and the constraint conditions of the freight machinery equipment model comprise: limit movement mileage and maximum rotation angle of the freight mechanical equipment;
the physical features of the freight park model include: the area, elevation and position of the production house, and the constraint conditions of the freight park model comprise site red lines and building height limits;
the system comprises a park information acquisition module, a freight park information generation module and a freight park information generation module, wherein the park information acquisition module is used for acquiring park information of a freight park, modeling the freight park through BIM and generating a freight park model, and setting material properties, physical characteristics and constraint conditions of the freight park model;
the simulation module is used for carrying out BIM simulation of the whole process of arriving at the container and sending the container according to the freight mechanical equipment model and the freight park model, generating time T required by transportation of multi-type intermodal transportation, acquiring the fatigue limit times of the freight mechanical equipment according to the material properties of the freight mechanical equipment model, and calculating maintenance time required by the freight mechanical equipment according to the fatigue limit times, wherein the time T comprises unloading time, loading time and transportation time;
the optimal transportation route calculation module is used for calculating the optimal transportation route in the freight park according to the modeling of the freight mechanical equipment and the freight park model and combining with an ant colony algorithm, wherein a new heuristic function is set, the ant colony algorithm is adjusted,
wherein setting a new heuristic function comprises: road traffic index
Figure QLYQS_30
And the traffic difficulty coefficient of the road->
Figure QLYQS_31
And calculating the equivalent length of the container transportation path +.>
Figure QLYQS_32
According to equivalent length->
Figure QLYQS_33
Setting a new heuristic function
Figure QLYQS_34
；
Setting a new heuristic function based on the equivalent length comprises:
calculating road traffic index
Figure QLYQS_35
，
Figure QLYQS_36
，
t is the time for the ant to move from node i to node j,
Figure QLYQS_37
for the road visibility influence coefficient from node i to node j, +.>
Figure QLYQS_38
An influence coefficient between trucks transporting containers from node i to node j;
coefficient of difficulty in passing
Figure QLYQS_39
，
Figure QLYQS_40
，
Figure QLYQS_41
For the current speed of a truck transporting containers in a freight park +.>
Figure QLYQS_42
The speed of the truck transporting the container when unobstructed in the freight park;
equivalent length of
Figure QLYQS_43
，
Figure QLYQS_44
，
Figure QLYQS_45
Is the geometric length of the channel in the freight park;
heuristic function
Figure QLYQS_46
，
Figure QLYQS_47
，
Equivalent length of
Figure QLYQS_48
The smaller the ant colony algorithm, the higher the heuristic, so that the optimal transportation route is selected.
5. The BIM-based dynamic optimization system of intermodal transportation of claim 4, wherein calculating the maintenance time required for the cargo machinery includes:
Figure QLYQS_49
，
wherein:
Figure QLYQS_50
for the operating time of the freight-machine, N is the number of fatigue limits of the freight-machine in the material properties, +.>
Figure QLYQS_51
Is a safety factor.
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