CN114662884A - A method of international multimodal transport based on risk assessment model - Google Patents

Abstract

The invention discloses an international multimodal transport method based on a risk assessment model, comprising the following steps: setting appropriate parameters according to known transport network information, and establishing a risk assessment model. Calculate the risk control cost according to the risk assessment model, combine the transportation cost and the carbon value cost, and obtain the total penalty cost model as the constraint condition. Aiming at the original Black Widow algorithm, a new H-BWO algorithm was formed to optimize the path planning of international multimodal transport by mixing chaos to optimize the population opening and adding an iterative speed control factor. Finally, a risk avoidance method of multimodal transport is proposed. The invention can realize the control of the total cost in the process of international multimodal transport, especially the risk cost brought by different routes and different transportation modes, and can better ensure the low-carbon nature of international multimodal transport, which is beneficial to the development of green in my country. Logistics has a certain driving effect.

Description

An International Multimodal Transport Method Based on Risk Assessment Model

technical field

The invention relates to an intermodal transport method, in particular to an international multimodal transport method based on a risk assessment model, and belongs to the technical field of transport path planning.

Background technique

Multimodal operation is a transportation method in which two or more vehicles are connected to each other to complete the transportation process. It can give full play to the advantages of different transportation methods and avoid the inaccessibility, uneconomical and poor reliability of traditional transportation methods. defect. However, the path planning of multimodal transport is also more complicated. Since two or more transport modes are involved, it usually requires longer transport time and greater transport risks. The transport mode should also be considered. Logistics transfer during the connection process. At the same time, the present invention proposes to use positioning technology to calculate the distance from the transport vehicle to the key node of the path where congestion or other high-risk reasons have occurred, and to take different measures according to the size of the distance. risk aversion approach.

At present, the existing multimodal transportation planning methods include ant colony algorithm, particle swarm algorithm, difference algorithm, etc. These methods often have slow convergence speed, cannot reach the global optimum, and require high prior knowledge of the environment. Occupying a large storage space and other problems, once a complex and dynamic environment is encountered, the efficiency of this type of planning method will drop significantly. In contrast, the black widow algorithm is inspired by the unique mating behavior of black widow spiders, and has the advantages of few control parameters, fast convergence speed, simple calculation and easy implementation.

The black widow algorithm simulates the life cycle of black widow spiders. Males use sex pheromones to identify female mating status. Because females display cannibalistic behavior, males are not interested in starving or malnourished females. The mechanism of the black widow algorithm is to make decisions and optimize through the unique movement and mating behavior of black widow spiders. It is simple and efficient, and is suitable for application in path planning and other problems, which makes the black widow algorithm very suitable for multimodal transportation. planning. However, in the original black widow algorithm, as the number of iterations increases, the fluctuation of the change will gradually decrease, which will lead to a local optimum. .

SUMMARY OF THE INVENTION

Aiming at the problems existing in the prior art, the present invention proposes an international multimodal transport method based on a risk assessment model, which improves the global search capability and the convergence speed, not only optimizes the planning scheme of the multimodal transport, but also can be more compatible with the The actual situation is closely integrated to enhance the practicality.

The present invention proposes an international multimodal transport method based on a risk assessment model, comprising the following steps:

Step 1. Establish a risk assessment model; establish a risk index table and transportation network information according to the actual transportation situation, set appropriate parameters, and establish a risk assessment index model;

Step 2. Calculate the risk control cost according to the risk assessment index model established in step 1, and combine the comprehensive transportation cost and carbon value cost to obtain the total penalty cost model as a constraint condition;

Step 3. Expand and improve the black widow algorithm BWO; design a new H-BWO algorithm by optimizing the population opening by mixing chaos and adding an iterative speed control factor;

Step 4. Generate a global optimal path according to the H-BWO algorithm in step 3, and set the basic parameters of the H-BWO algorithm: combine the minimum penalty cost function model to generate a global optimal path as the current global path for multimodal transport Proposal;

Step 5. Propose a risk avoidance method for multimodal transport; for the key nodes of the path where congestion or other high-risk reasons have occurred, different risk avoidance methods are adopted in combination with the distance from the transport vehicle to the key node.

The present invention effectively controls the above three aspects by constructing corresponding penalty cost functions for the risk control cost, comprehensive transportation cost and carbon value cost in the process of multimodal transportation, and forming a unified minimum penalty cost model as a constraint , in order to achieve the comprehensive optimal. Moreover, considering the high and uncertainty in the process of international multimodal transport, a corresponding risk index table has been established to deal with the risks brought by different routes and different modes of transport, so as to achieve a more realistic and targeted application. modeling to solve the problem.

Further, in the step 1, the risk index table includes the risk index of the transport mode, the risk index of the transport route and the risk index of the transported items;

The transportation means at least include air transportation, railway transportation, road transportation, pipeline transportation, inland shipping and sea transportation;

The transportation route includes key road sections at different levels such as provincial boundaries, national boundaries and continental boundaries;

The transported items include ores, energy, agricultural products, high-tech products, industrial supplies and medical supplies.

Further, according to the international logistics and transportation network data, the connection model of each node in the transportation network under each transportation mode is established, and the following model is obtained by considering whether the node i can reach the node j:

i,j∈N; i<j;

表示从i点到j点用w类运输方式；N表示为所有节点的集合。in,

Indicates the w-type transportation mode from point i to point j; N represents the set of all nodes.

Further, a risk assessment index model of multimodal transport is established in combination with the risk index table, and the risk assessment index of multimodal transport is related to the types of transported items, transport routes, and transport modes during the transportation process. Therefore, the following risk assessment index model is established: using the actual path data combined with the parameters of the risk assessment table, a risk assessment model based on the risk assessment table is established:

表示第i点到第j点用w类运输方式的风险指数；D_ij表示第i点到第j点运输路径的风险指数；θ_q表示运输q类物品的风险指数。Among them, K represents the total risk index of the transportation process;

Represents the risk index of the w-type transportation method from point i to point j; D _ij represents the risk index of the transportation route from point i to point j; θ _q represents the risk index of transporting q-type items.

Further, for the established risk assessment index model, the risk is controlled within an acceptable range by means of insurance, risk management, etc., resulting in the cost of risk control. The risk control cost is generated from this; the risk control cost is classified and discussed, and two risk control thresholds T ₁ and T ₂ are set, as well as two risk cost control indices Φ and δ. Judging, the risk control costs are as follows:

Among them, T ₁ and T ₂ are risk control thresholds, and the values can be set by the user according to the actual situation; Φ, δ are risk control cost parameters, Φ∈[1,2], δ∈[2,3].

Further, a transportation cost model based on the entropy increase system is established; the transportation cost of multimodal transportation is reflected in the direct transportation cost related to the transportation quantity, time and distance, and the indirect transportation cost related to the transit and management during the transportation process. Since the overall process of multimodal transportation reflects the same phenomenon as the law of entropy increase in physics, that is, with the increase of transportation time, transportation distance and transit nodes, the chaos of transportation will increase accordingly, and certain management and control must be added. Cost can effectively reduce the disorder of transportation. Therefore, the following transportation cost model is established based on the law of entropy increase:

Among them, L _ij represents the transportation distance from the i-th point to the j-th point; U _w represents the unit distance cost of the w-type transportation method from the i-th point to the j-th point; G represents the quantity or quality or volume of the transported items.

Further, a carbon value cost model is established. The carbon value cost is related to the transportation volume and distance in the transportation process. Therefore, the following transportation cost model is established:

Among them, λ represents the cost parameter of carbon emission; εw represents the unit carbon emission of the _w type of transportation.

Further, appropriate weights are taken for the aforementioned three costs, and a minimum penalty cost model based on the risk assessment model, the efficiency assessment model and the carbon value cost is established, and its expression function is:

MinC=α*C ₁ +β*C ₂ +γ*C ₃ ;

α+β+γ=1, α, β, γ∈[0,1];

Among them, C is the total evaluation value of the multimodal transport process; _C1 is the risk control cost of the multimodal transport process; _C2 is the transportation cost _of the multimodal transport process; C3 is the carbon value cost of the multimodal transport process; α, β and γ are the weight parameters of the three evaluation values.

Further, in the step 4, according to the minimum penalty cost function model, the specific steps of generating a global optimal path through the H-BWO algorithm are as follows:

Step 4.1. Initialize H-BWO algorithm parameters:

The parameters of the initialized H-BWO algorithm include: population size D, the maximum number of iterations Z, randomly generated parameters m, Ω and r. The chaotic mechanism is introduced to optimize the population opening of the H-BWO algorithm, so that the initial population distribution can be fully utilized. The entire algorithm space maximizes the information utilization of the algorithm space, and also has good guidance, so as to speed up the convergence speed of the algorithm and avoid local optimization; the regularity, randomness and ergodicity of chaotic sequences are used to make the algorithm. The initial population of the H-BWO algorithm can utilize the information of the search space as much as possible:

Among them, a, b are chaotic constants, a∈(0,1.4), b∈(0.2,0.314];

Step 4.2, H-BWO algorithm position update:

The black widow spider moves in a linear and helical manner within the grid, and the position is updated as follows:

Step 4.3, calculate the pheromone rate value:

Pheromone plays a very important role in the courtship process of spiders, and male spiders do not like female spiders with low pheromone content; the formula for the pheromone rate of black widow spiders is as follows:

Among them, A _i represents the pheromone rate value of the black widow spider; f _max and f _min are the worst and optimal fitness function values; f _i is the fitness value obtained by the ith black widow;

Step 4.4. Update the position of the black widow with low pheromone rate value: change the original BWO position iteration formula and add an iterative speed control factor to slow down the speed of the BWO algorithm at the beginning of the iteration to avoid local optimization; at the same time, as the number of iterations gradually increases, The convergence speed is effectively accelerated.

When the pheromone rate value is equal to or less than 0.3, spiders with low pheromone levels in females represent hungry cannibal spiders; therefore, if they are present, the female spiders mentioned above will not be selected, but will be replaced by another; thus targeting the location The iterative formula is improved, and the iterative speed control factor τ is added to make it have good guidance, so as to control the convergence speed of the algorithm, avoid the local optimal situation in the early stage, and speed up the convergence speed of the algorithm in the later stage. The improved formula is as follows :

Among them, P _i (t) is the current black widow position or the black widow position with low pheromone rate value; P _i (t+1) is the updated black widow position; P _b is the current optimal position of the black widow; P _r1 (t) and P _r2 (t) are the positions of the random r ₁ and r ₂ black widows, r ₁ and r ₂ are numbers in the range of [1, D], r ₁ ≠r ₂ ; τ is the iteration Speed control factor; n is the current iteration number; Z is the maximum iteration number of the H-BWO algorithm; η is a random binary number {0, 1};

Step 4.5, re-evaluate the fitness function value, and update the position of the optimal black widow and the optimal solution;

Step 4.6: Determine whether the maximum number of iterations is satisfied. If the algorithm reaches the maximum number of iterations Z, output the optimal black widow position and the global optimal solution, otherwise return to step 4.2 to re-iteratively calculate.

Aiming at the key nodes of the path where congestion or other high-risk reasons have occurred, the present invention proposes to use the positioning technology to calculate the distance ξ from the transport vehicle to the key nodes of the path where congestion or other high-risk reasons occur, and take different measures according to the calculated distance. method of risk aversion. When e≥100km, update the logistics information network and remove the key node, and then re-plan the path through the H-BWO algorithm; when 10km≤e<100km, the transport vehicle can stop moving forward, waiting for congestion or other high risks to be reduced Further arrangements will be made in the future.

Compared with the prior art, the beneficial effects of the present invention are: the present invention mixes chaos to optimize the population opening and adds an iterative speed control factor, thereby forming a new H-BWO algorithm, which has a better opening and can reduce the algorithm The information utilization of space is maximized. At the same time, it also has good guidance, so as to control the convergence speed of the algorithm, avoid the occurrence of local optimum in the early stage, and speed up the convergence speed of the algorithm in the later stage. After introducing the minimum penalty cost model, the global optimal path is generated by the H-BWO algorithm, which can realize the control of the total cost in the process of international multimodal transportation, especially the risk cost caused by different paths and different transportation methods, and can be more Ensuring the low-carbon nature of international multimodal transport will play a certain role in promoting the development of green logistics in my country.

Description of drawings

FIG. 1 is a flow chart of the present invention.

Fig. 2 is the flow chart of H-BWO algorithm in the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but not to be construed as a limitation of the present invention.

An international multimodal transport method based on a risk assessment model proposed in this embodiment includes the following specific steps:

1. Minimum penalty cost function modeling

Assume that the relevant logistics information is input: the transported items are agricultural products; the transport origin is Iowa, USA, and the destination is Wuhan, China. Combined with the relevant data of the risk index evaluation table of different transportation methods, the risk index evaluation table of key sections of the transportation route, and the risk index evaluation table of different transportation items, the basic parameters are as follows: Φ=1.5, δ=2.5, T ₁ = 10, T ₂ =20, θ _i =3, λ = 0.5. Form a comprehensive minimum penalty cost model such as:

MinC=0.5*C ₁ +0.3*C ₂ +0.2*C ₃

The constraints are as follows:

i,j∈N; i<j;

Among them, the risk index evaluation table is as follows:

According to the actual transportation situation, corresponding risk index tables have been established for different main transportation modes such as air transportation, railway transportation, road transportation, pipeline transportation, inland waterway shipping, and sea transportation. The table is as follows:

Table 1. Risk index assessment table for different modes of transport

At the same time, according to the actual situation, a risk index table is constructed for the key sections of the transportation route, and the risk index evaluation is carried out for key sections of different levels such as provincial boundaries, national boundaries, and continental boundaries, especially for transportation through world-class transportation hubs and major roads. Path evaluation. The table is as follows:

Table 2. Risk index assessment table for key sections of transportation routes

In addition, according to the actual situation, a risk index table for different transported items is constructed, and risk index assessment is carried out for ores, energy, agricultural products, high-tech products, etc., especially for industrial supplies and fossil energy.

Table 3. Risk index assessment table for different transported items

2. Improve the algorithm and solve

In the process of planning the distribution path of international multimodal transport, the present invention introduces chaos, changes the original BWO position iteration formula, and improves the BWO algorithm in many aspects such as population opening optimization, thereby forming a new H -BWO algorithm to solve the minimum penalty cost model. The H-BWO algorithm finds an optimal path among many paths through calculation.

1) Initialize H-BWO algorithm parameters

The parameters of the initialized H-BWO algorithm include: population size D, maximum number of iterations Z, randomly generated parameters m, Ω and r. The chaotic mechanism is introduced to optimize the population opening. Using the regularity, randomness and ergodicity of the chaotic sequence, the initial population of the H-BWO algorithm can use the information of the search space as much as possible:

2) H-BWO algorithm location update

The black widow spider moves in a linear and helical manner within the grid, and the position is updated as follows:

3) Calculate the pheromone rate value

Pheromone plays a very important role in the courtship process of spiders, and male spiders do not like female spiders with low pheromone content. The formula for the pheromone rate value of the black widow spider is as follows:

4) Update black widow position with low pheromone rate value

When the pheromone rate value is equal to or less than 0.3, spiders with low pheromone levels in females represent hungry cannibal spiders. Therefore, if they are present, the female spiders mentioned above will not be selected, but will be replaced by another. Here, the present invention improves the position iteration formula, and adds an iterative speed control factor τ to make it have good guidance, so as to control the convergence speed of the algorithm, avoid the situation of local optimum in the early stage, and speed up the later stage. The convergence speed of the algorithm, the improved formula is as follows:

5) Re-evaluate the fitness function value, and update the position of the optimal black widow and the optimal solution.

6) The algorithm terminates

If the algorithm reaches the maximum number of iterations Z, output the optimal black widow position and the global optimal solution, otherwise return to step 2 to re-iterate the calculation.

The results calculated by the H-BWO algorithm: from Iowa to the Port of Los Angeles by rail, transferred to the port of Shanghai, China by sea, and then to Wuhan along the Yangtze River via inland shipping.

It can be seen from the calculation results that the H-BWO algorithm formed by mixing chaos and adding an iterative speed control factor τ can effectively improve the convergence speed and global optimization ability of the BWO algorithm and avoid falling into local optimum. In view of the complex situation of international multimodal transport, the H-BWO algorithm combines the minimum penalty cost model to generate a global optimal path, which can effectively control the risks in the process of international multimodal transport, and can further reduce carbon emissions. The green logistics industry plays a role in promoting development.

It should be noted that the above-described embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by those skilled in the art without departing from the scope of the appended claims.

Claims (9)

1. an international multimodal transport method based on risk assessment model, is characterized in that: comprise the steps: Step 1. Establish a risk assessment model; establish a risk index table and transportation network information according to the actual transportation situation, set appropriate parameters, and establish a risk assessment index model; Step 2. Calculate the risk control cost according to the risk assessment index model established in step 1, and combine the comprehensive transportation cost and carbon value cost to obtain the total penalty cost model as a constraint condition; Step 3. Expand and improve the black widow algorithm BWO; design a new H-BWO algorithm by optimizing the population opening by mixing chaos and adding an iterative speed control factor; Step 4. Generate a global optimal path according to the H-BWO algorithm in step 3, and set the basic parameters of the H-BWO algorithm: combine the minimum penalty cost function model to generate a global optimal path as the current global path for multimodal transport Proposal; Step 5. Propose a risk avoidance method for multimodal transport; for the key nodes of the path where congestion or other high-risk reasons have occurred, different risk avoidance methods are adopted in combination with the distance from the transport vehicle to the key node. 2. The international multimodal transport method based on a risk assessment model according to claim 1, wherein in the step 1, the risk index table includes the risk index of the mode of transport, the risk index of the transport route and the risk of the transported goods index; The transportation means at least include air transportation, railway transportation, road transportation, pipeline transportation, inland shipping and sea transportation; The transportation route includes key road sections at different levels such as provincial boundaries, national boundaries and continental boundaries; The transported items include ores, energy, agricultural products, high-tech products, industrial supplies and medical supplies. 3. the international multimodal transport method based on risk assessment model according to claim 1, is characterized in that: establish the connectivity model of each node in the transport network under each mode of transport according to the international logistics transport network data, considering whether from node i In the case of being able to reach node j, the following model is derived:

in,

Indicates the w-type transportation mode from point i to point j; N represents the set of all nodes. 4. the international multimodal transport method based on risk assessment model according to claim 2, is characterized in that: combine the risk index in the risk index table, establish the risk assessment index model of multimodal transport: utilize actual path data, combine risk Evaluate the parameters of the table to establish a risk assessment model based on the risk assessment table:

Among them, K represents the total risk index of the transportation process;

Represents the risk index of the w-type transportation method from point i to point j; D _ij represents the risk index of the transportation route from point i to point j; θ _q represents the risk index of transporting q-type items. 5. The international multimodal transport method based on a risk assessment model according to claim 4, characterized in that: for the established risk assessment index model, at least by means of insurance and risk management, the risk scope is controlled, thereby generating risk control cost. The risk control cost is classified and discussed, and two risk control thresholds T ₁ and T ₂ are set, and two risk cost control indexes Φ and δ are used to classify and judge different transportation risks in different situations. The risk control cost as follows:

Among them, T ₁ and T ₂ are risk control thresholds, and the values can be set by the user according to the actual situation; Φ, δ are risk control cost parameters, Φ∈[1,2], δ∈[2,3]. 6. The international multimodal transport method based on risk assessment model according to claim 1, is characterized in that: in the step 2, the transport cost model is established based on the entropy increase system; Direct transportation costs related to transportation quantity, time, and distance, and indirect transportation costs related to transit and management; because the overall process of multimodal transportation reflects the same phenomenon as the law of entropy increase in physics, that is, with transportation time, transportation distance And with the increase of transit nodes, the disorder of transportation will increase accordingly. Certain management and control costs must be added to effectively reduce the disorder of transportation. Therefore, the following transportation cost model is established based on the law of entropy increase:

Among them, L _ij represents the transportation distance from the i-th point to the j-th point; U _w represents the unit distance cost of the w-type transportation method from the i-th point to the j-th point; G represents the quantity or quality or volume of the transported items. 7. The international multimodal transport method based on a risk assessment model according to claim 1, characterized in that: in the step 2, the carbon value cost is related to the transport volume and distance in the transport process, so the following transport cost model is established :

Among them, λ represents the cost parameter of carbon emission; εw represents the unit carbon emission of the _w type of transportation. 8. the international multimodal transport method based on risk assessment model according to claim 5 or 6 or 7, is characterized in that: establish the minimum penalty cost model based on risk assessment model, efficiency assessment model and carbon value cost, and its expression function for: MinC=α*C ₁ +β*C ₂ +γ*C ₃ ; α+β+γ=1, α, β, γ∈[0,1]; Among them, C is the total evaluation value of the multimodal transport process; _C1 is the risk control cost of the multimodal transport process; _C2 is the transportation cost _of the multimodal transport process; C3 is the carbon value cost of the multimodal transport process; α, β and γ are the weight parameters of the three evaluation values. 9. The international multimodal transport method based on risk assessment model according to claim 1, is characterized in that: in the described step 4, according to the minimum penalty cost function model, the concrete of a global optimal path is generated by H-BWO algorithm. Proceed as follows: Step 4.1. Initialize H-BWO algorithm parameters: The parameters of the initialized H-BWO algorithm include: population size D, the maximum number of iterations Z, randomly generated parameters m, Ω and r, in which the chaotic mechanism is introduced to optimize the population opening; the regularity, randomness and ergodicity of the chaotic sequence are used, etc. The characteristics enable the initial population of the H-BWO algorithm to utilize the information of the search space as much as possible:

Among them, a, b are chaotic constants, a∈(0,1.4), b∈(0.2,0.314]; Step 4.2, H-BWO algorithm position update: The black widow spider moves in a linear and helical manner within the grid, and the position is updated as follows:

Step 4.3, calculate the pheromone rate value: Pheromone plays a very important role in the courtship process of spiders, and male spiders do not like female spiders with low pheromone content; the formula for the pheromone rate of black widow spiders is as follows:

Among them, A _i represents the pheromone rate value of the black widow spider; V _max and V _min are the worst and optimal fitness function values; f _i is the fitness value obtained by the ith black widow; Step 4.4, update the black widow position with low pheromone rate value: When the pheromone rate value is equal to or less than 0.3, spiders with low pheromone levels in females represent hungry cannibal spiders; therefore, if they are present, the female spiders mentioned above will not be selected, but will be replaced by another; thus targeting the location The iterative formula is improved, and the iterative speed control factor τ is added to make it have good guidance, so as to control the convergence speed of the algorithm, avoid the local optimal situation in the early stage, and speed up the convergence speed of the algorithm in the later stage. The improved formula is as follows :

Among them, P _i (t) is the current black widow position or the black widow position with low pheromone rate value; P _i (t+1) is the updated black widow position; P _b is the optimal position of the current black widow; P _r1 (t) and P _r2 (t) are the positions of the random r ₁ and r ₂ black widows, r ₁ and r ₂ are numbers in the range of [1, D], r ₁ ≠r ₂ ; τ is the iteration Speed control factor; n is the current iteration number; Z is the maximum iteration number of the H-BWO algorithm; η is a random binary number {0, 1}; Step 4.5, re-evaluate the fitness function value, and update the position of the optimal black widow and the optimal solution; Step 4.6: Determine whether the maximum number of iterations is satisfied. If the algorithm reaches the maximum number of iterations Z, output the optimal black widow position and the global optimal solution, otherwise return to step 4.2 to re-iteratively calculate.

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