A transport path optimization method and device considering port cascade failure risk

Abstract

The application discloses a kind of transport path optimization method and device considering port cascading failure risk, belong to port logistics and transport network optimization technical field.For the problem that insufficient consideration is given to port systemic risk in existing transport path planning, and chain reaction is easily caused by single point failure, the application proposes a comprehensive evaluation and optimization mechanism, by constructing a weighted directed graph model to represent the port transport network, integrating the port carrying capacity, historical failure probability and multi-dimensional external risk factors, the quantitative calculation of port cascading failure risk is realized.On this basis, a multi-objective optimization function is designed, with the minimum time and cost product as the optimization goal, while constraining the lowest probability of full-path failure risk, and using gradient descent algorithm to solve the optimal transport path.By dynamically adjusting the transport volume distribution, effectively avoiding high-risk nodes, the network robustness and transport reliability are improved.The application method can be widely applied to international sea transport, container scheduling and other scenarios, significantly reducing transport cost and interruption risk, and enhancing the ability to respond to emergencies.

Description

Technical Field

[0001] This invention relates to the field of port transportation network optimization, specifically to a transportation route optimization method and apparatus that considers the risk of port cascading failures. The aim is to optimize multiple transportation routes where both system failure risk and transportation costs are within an acceptable range, and it is applicable to scenarios such as international container shipping and bulk commodity sea freight. Background Technology

[0002] With the continuous development of global trade, ports, as crucial logistics nodes, play a vital role in ensuring the stable operation of the entire supply chain through the efficiency and security of their transportation networks. However, port transportation networks face various risks, such as equipment failures, natural disasters, and geopolitical risks. These risks can lead to cascading port failures, severely impacting transportation efficiency and costs. Therefore, a transportation route optimization method that considers the risks of cascading port failures is needed to improve the stability and efficiency of port transportation networks. Summary of the Invention

[0003] The purpose of this invention is to provide a transportation route optimization method and apparatus that considers the risk of port cascading failures. This invention comprehensively considers the influence of relevant factors such as port capacity, systemic risks, economic costs, and route distances, and conducts comprehensive evaluation and optimization algorithms on these factors to solve various risk problems faced by port transportation networks in the prior art. This ensures the reliability and economy of transportation schemes, achieves precise avoidance of port cascading failure risks, and improves logistics transportation efficiency.

[0004] To achieve the above-mentioned objectives, the transportation route optimization method of the present invention, which considers the risk of port cascading failures, includes:

[0005] S1. Port transportation network model construction and data collection, mainly including the following parts:

[0006] S11: Construct a weighted directed port transportation network model based on graph theory, port network ,in For the set of port nodes, This represents the n port nodes in network G. This is the set of distances between ports. Indicates port to port distance, This represents the set of edge weights between ports, which can also be understood as the existing transportation volume between ports. Indicates port to port Current network traffic volume;

[0007] S12: Collect port network Each port in China Various key data, including the port's maximum capacity Probability of past failures Equipment Failure Early Warning Impact of natural disasters Geopolitical risks .

[0008] S2. Port cascading failure risk assessment mainly includes the following parts:

[0009] S21: Calculation Path In the context of port i carrying capacity risk probability As shown in the following formula:

[0010]

[0011] in, This represents the load migration capacity of port i. That is, the carrying capacity of port i in port network G that is migrated from other ports. This represents the volume of transport along the original ji route. This indicates the maximum carrying capacity of port i;

[0012] S22: Calculate the non-carrying risk probability of port i As shown in the following formula:

[0013]

[0014] in, , , These represent the collected probabilities of equipment failure warnings, natural disaster impacts, and geopolitical risks at port i, respectively. This indicates the non-carrying risk dimension, which can be determined based on the collected risk data;

[0015] S23: Calculate the failure risk probability of port i. As shown in the following formula:

[0016]

[0017] in, This represents the probability of past failures for port i that has been collected. Let i be the probability of risk related to port capacity. Let be the probability of non-carrying risk for port i.

[0018] S3. Multi-objective path optimization calculation between ports mainly includes the following parts:

[0019] S31: Solve the multi-objective path optimization function using multi-objective fitting methods, including but not limited to gradient descent. As shown in the following formula:

[0020]

[0021] in, This represents the time function for solving the optimal path. This represents the cost function for solving the optimal path. The function represents the minimum product of time and cost, and its formula is as follows:

[0022]

[0023] in, Indicates the optimized path The distance between ports in the middle Indicates the optimized path The distance and, Represents the ocean speed constant. Indicates the optimized path The product of the distance between Chinese and foreign ports and the volume of cargo transported. This represents a constant representing the unit cost of ocean freight.

[0024] Solution conditions The following formula represents the minimum probability of failure for all ports in the global region G:

[0025]

[0026] in, This represents the probability of failure for port i. It is a natural constant. Indicates the optimized path The terminal port in the middle, Indicates the optimized path The number of ports in the country;

[0027] S32: Optimization scheme formulation, based on the optimized path set obtained from the solution. The optimal transportation volume scheme between ports was obtained. As shown in the following formula:

[0028]

[0029] in, This represents the original transport volume from port i to port j. This represents the optimal transport volume from port i to port j.

[0030] The present invention also provides a transportation route optimization device that considers the risk of port cascading failures, comprising: a construction unit for constructing a port transportation network model and collecting data; a calculation unit for calculating the risk of port cascading failures; and a calculation unit for calculating multi-objective route optimization between ports.

[0031] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0032] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0033] The transportation route optimization method in this application, which considers the risk of port cascading failures, has the following advantages:

[0034] 1. Improve the reliability of port transportation networks: By constructing port transportation network models and considering the risk of cascading port failures, potential risk points in the port network can be effectively identified and assessed, thereby developing more reliable transportation routes and reducing the risk of the entire network being paralyzed due to the failure of a single port.

[0035] 2. Optimize transportation routes and reduce costs and time: This invention uses multi-objective path optimization calculations to solve for the minimum function that minimizes the product of time and cost, based on risk probability, thereby obtaining the optimal transportation route.

[0036] 3. Enhanced ability to respond to emergencies: This invention considers a variety of risk factors, including equipment failure, natural disasters and geopolitical risks. By quantifying and assessing these risks, it can better respond to emergencies and reduce transportation disruptions and delays caused by emergencies.

[0037] 4. Enhance the carrying capacity of the port network: By calculating the risk probability of port carrying capacity, the transportation volume of each port can be monitored and adjusted in real time to avoid port failure due to overload operation. Attached Figure Description

[0038] Figure 1 This is the overall flowchart of the method;

[0039] Figure 2 This is an example diagram of a directed transportation network model. Detailed Implementation

[0040] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0041] This implementation plan optimizes existing port transportation routes. By considering factors such as carrying capacity, past failure probabilities, equipment failure warning probabilities, natural disaster impacts, and geopolitical risks, the original routes are optimized using the cascaded failure risk method of this invention. The failure risk probabilities of each port and the overall system are recalculated to obtain the optimized transportation routes. A specific example is as follows:

[0042] There is a port with 5 ports , , , , The transportation network, including the volume of traffic and distances between ports, is known. Specific data is as follows:

[0043] Transportation volume matrix W:

[0044]

[0045] Distance matrix E:

[0046]

[0047] Maximum carrying capacity H of each port:

[0048]

[0049] Probability of failure risk at each port in the past (Q):

[0050]

[0051] Probability of equipment failure warning for each port (B):

[0052]

[0053] The probability Z of natural disaster impact on each port:

[0054]

[0055] Geopolitical risk probability of various ports :

[0056] Step S1: Port transportation network model construction and data collection

[0057] Based on the above data, a port transportation network model is constructed. .

[0058] Step S2: Port Cascade Failure Risk Assessment

[0059] S21: Calculate the port capacity risk probability

[0060] For some reason, the port The load needs to be relocated to other ports. Calculate the load relocation capacity of each port. ,in Port carrying capacity risk probability for:

[0061]

[0062] S22: Calculate the probability of non-capacity risk at the port

[0063]

[0064] S23: Calculate the port's failure risk probability

[0065]

[0066] Step S3: Multi-objective path optimization calculation between ports

[0067] S31: Solve the multi-objective path optimization function using methods not limited to gradient descent.

[0068] Calculate the time function of the optimized path and cost function The optimized path is

[0069] Then the product of port distance and cargo volume in the path are respectively:

[0070]

[0071]

[0072] Ocean speed constant Section, constant unit cost of ocean freight At $100 per unit distance per unit volume, then:

[0073] Minimum function of time and cost product :

[0074]

[0075] Calculate the global failure risk probability

[0076] Failure risk probability of each port :

[0077] Calculate the global failure risk probability:

[0078] Calculate the objective function :

[0079]

[0080] S32: Optimization Plan Formulation

[0081] Based on the optimized path set obtained from the solution The optimal transportation volume scheme between ports was obtained. :

[0082]

[0083] Calculate the optimal transport volume between ports. :

[0084] The present invention also provides a transportation route optimization device that considers the risk of port cascading failures, comprising: a construction unit for constructing a port transportation network model and collecting data; a calculation unit for calculating the risk of port cascading failures; and a calculation unit for calculating multi-objective route optimization between ports.

[0085] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method steps. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0086] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0087] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A transportation route optimization method considering the risk of port cascading failures, characterized in that, Includes the following steps: S1: Port transportation network model construction and data collection; including: constructing a weighted directed port transportation network model based on graph theory, and port network... ,in For the set of port nodes, This represents the n port nodes in network G. This is the set of distances between ports. Indicates port to port distance, Let the set of edge weights between ports be denoted as . Indicates port to port Current network traffic volume; S2: Port Cascade Failure Risk Assessment; including: S21: Calculation Path In the middle, the port i carrying capacity risk probability As shown in the following formula: in, This represents the load migration capacity of port i. That is, the carrying capacity of port i in port network G that is migrated from other ports. This represents the volume of transport along the original ji route. This indicates the maximum carrying capacity of port i; S22: Calculate the non-carrying risk probability of port i As shown in the following formula: in, , , These represent the collected probabilities of equipment failure warnings, natural disaster impacts, and geopolitical risks at port i, respectively. This indicates the non-carrying risk dimension, which can be determined based on the collected risk data; S23: Calculate the failure risk probability of port i. As shown in the following formula: in, This represents the probability of past failures for port i that has been collected. Let i be the probability of risk related to port i's carrying capacity. Let i be the probability of non-carrying capacity risk. S3: Multi-objective path optimization calculation between ports; including: solving the multi-objective path optimization function. As shown in the following formula: in, This represents the time function for solving the optimal path. This represents the cost function for solving the optimal path. This represents the function that minimizes the product of solution time and cost. This indicates that the probability of failure for all ports in the global G is minimized.

2. The method according to claim 1, characterized in that, Step S1, port transportation network model construction and data collection, includes: S12: Collect port network Each port in China Various key data, including the port's maximum capacity ,in It is the maximum carrying capacity of the nth port and the probability of past failures. ,in It is the probability of past failures and early warning of equipment malfunctions for the nth port. ,in It is the early warning of equipment failure and the impact of natural disasters at the nth port. ,in The impact of natural disasters on the nth port, and the geopolitical risk g. ,in This refers to the geopolitical risks of the nth port.

3. The method according to claim 1, characterized in that, Step S3, the multi-objective path optimization calculation between ports, includes: S31: The formula for calculating the function is as follows: in, Indicates the optimized path The distance between ports in the middle Indicates the optimized path The distance and, Represents the ocean speed constant. Indicates the optimized path The product of the distance between Chinese and foreign ports and the volume of cargo transported. This represents a constant representing the unit cost of ocean freight. Solution conditions As shown in the following formula: in, This represents the probability of failure for port i. It is a natural constant. Indicates the optimized path The terminal port in the middle, Indicates the optimized path The number of ports in the country; S32: Optimization scheme formulation, based on the optimized path set obtained from the solution. The optimal transportation volume scheme between ports was obtained. As shown in the following formula: in, This represents the original transport volume from port i to port j. This represents the optimal transport volume from port i to port j.

4. A transportation route optimization device considering the risk of port cascading failures, characterized in that, include: Building blocks are used for port transportation network model building and data collection; A weighted directed port transportation network model is constructed based on graph theory. ,in For the set of port nodes, This represents the n port nodes in network G. This is the set of distances between ports. Indicates port to port distance, Let the set of edge weights between ports be denoted as . Indicates port to port Current network traffic volume; The calculation unit is used for calculating the risk of cascading failures in ports. Calculation path In the middle, the port i carrying capacity risk probability As shown in the following formula: in, This represents the load migration capacity of port i. That is, the carrying capacity of port i in port network G that is migrated from other ports. This represents the volume of transport along the original ji route. This indicates the maximum carrying capacity of port i; Calculate the non-carrying risk probability of port i As shown in the following formula: in, , , These represent the collected probabilities of equipment failure warnings, natural disaster impacts, and geopolitical risks at port i, respectively. This indicates the non-carrying risk dimension, which can be determined based on the collected risk data; Calculate the failure risk probability of port i As shown in the following formula: in, This represents the probability of past failures for port i that has been collected. Let i be the probability of risk related to port i's carrying capacity. Let i be the probability of non-carrying capacity risk. The computing unit is used for multi-objective path optimization calculations between ports, solving for the multi-objective path optimization function. As shown in the following formula: in, This represents the time function for solving the optimal path. This represents the cost function for solving the optimal path. This represents the function that minimizes the product of solution time and cost. This indicates that the probability of failure for all ports in the global G is minimized.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method described in any one of claims 1-3.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1-3.

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