CN110334977B - Traffic distribution method for port cluster container collecting and distributing system - Google Patents
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Abstract
The invention discloses a traffic distribution method of a port cluster container collecting and distributing system, which comprises the following steps: s01, abstracting an undirected graph containing nodes and edges according to the harbor relations in the harbor cluster container centralized distribution system; s02, establishing a traffic distribution model of the port cluster container distribution system, wherein the traffic distribution model is used for minimizing and calculating the sum of direct transportation cost and transfer cost, and additionally establishing constraint conditions to ensure that the transportation volume and time of each stage in the transportation process meet the requirements; s03, an algorithm of a traffic distribution model of the port cluster container distribution system is solved, the incremental distribution method is adopted to gradually distribute and solve the road network flow, and a Dijkstra algorithm is adopted during distribution. The invention provides a traffic distribution method for a port cluster container collecting and transporting system, which is used for establishing a dynamic traffic distribution model for the port cluster container collecting and transporting system in various transportation modes by considering road impedance factors so as to provide theoretical support for regional road network planning and traveling.
Description
Technical Field
The invention relates to a traffic flow distribution method of a port cluster container collecting and distributing system, belonging to the technical field of port cluster logistics.
Background
With the vigorous push of the national 'one-by-one' initiative, coastal port throughput is rising year by year. The annual increase rates of Shanghai, Ningbo-Zhoushan and Shenzhen hong 2018 are 4201, 2635 and 2574 million TEU respectively, and 4.4%, 6.9% and 7.6% respectively. Good performance of coastal ports puts higher and higher requirements on land-oriented infrastructure matched with the ports, and the national strategy of 'adjustment of three-year action plan by propulsion transportation structure' in 2018 puts forward a requirement on greatly increasing the railway collection and distribution volume of the ports and the multi-type container combined transportation volume. How to efficiently and inexpensively distribute containers is one of the hot spots in the research of the port group distribution and transportation system.
The collection and distribution system is a branch of the transportation system, and most researches thereof intersect with the directions of traffic flow, transportation economy and the like. Especially, traffic distribution is widely applied to a collection and distribution system, and the main purpose of the system is to enable users to reasonably select travel paths or provide references for road network planners.
At present, the traffic distribution is mainly applied to the research of port cluster distribution systems in two aspects: 1) traffic flow distribution is only done on road traffic. 2) The traffic flow distribution is carried out on different transportation modes according to specific proportion.
Disclosure of Invention
The invention aims to provide a dynamic port cluster container collecting and distributing system traffic flow distribution method which considers road impedance factors and has various transportation modes, so as to provide theoretical support for regional road network planning and traveling.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a traffic distribution method for a port cluster container collecting and distributing system comprises the following steps:
s01, abstracting an undirected graph containing nodes and edges according to the harbor relations in the harbor cluster container centralized distribution system;
s02, establishing a traffic distribution model of the port cluster container distribution system, wherein the traffic distribution model is used for minimizing and calculating the sum of direct transportation cost and transfer cost, representing road impedance by a BPR function in the direct transportation cost, converting time in the BPR function into a cost form through transportation time value, and establishing a constraint condition to ensure that the transportation volume and time of each stage in the transportation process meet requirements;
s03, an algorithm for solving a traffic distribution model of the port cluster container centralized distribution system is adopted, incremental distribution is adopted to carry out gradual distribution solving on the traffic of the road network, in the gradual traffic distribution, an initial cost table of the road network is given through a generalized cost model, in each increment of the incremental distribution method, the incremental traffic of the nodes of the road network is distributed according to a given sequence and a minimum cost principle according to the cost table, and a Dijkstra algorithm is adopted during distribution.
In S01, the nodes in the undirected graph comprise a source city, a middle city, a road intersection, a transportation mode conversion point and a port; the edge comprises three transportation lines of male, iron and water transportation modes. In S02, the expression of the traffic distribution model is as follows:
wherein minC represents the minimum value of the sum of direct transportation cost and transfer cost; r is a container generation place set, S is a container destination port set, K is a set of all paths between a container generation place R and a port S and comprises different transportation modes, a road section a is positioned between two nodes, the road section a is only one transportation mode, a belongs to A, A is a set of all road sections, B can be any node between R and S, B belongs to B, and B is a set of all intermediate nodes;
is a decision variable, if the road segment a is on the kth road segment between r and s
Otherwise
Is a decision variable, if the goods are transferred in node b between r and s
Otherwise
Is the direct transportation cost for the kth road segment between r and s;
is the cost of transfer in node b between r and s;
in addition, the first and second substrates are,
and
the calculation method of (c) is as follows:
wherein the content of the first and second substances,
representing the value of unit transit time, t k Indicating the time of the shipment of the goods, in hours,
representing the flow of goods converted in node b between r and s, f tr The expression represents the transfer rate in transfer, tau represents the transfer coefficient,
represents the time of transfer in node b between r and s;
wherein the road resistance function t k Under different conditions, the method has different forms, in particular:
1) road transport impedance function
A BPR function is used, of the form:
where α, β are time-cost fit parameters of the BPR function, q k Indicating the flow of goods on section k, F k Representing the capacity of a section k, t free,k Representing free-stream travel time of a link k, calculatingThe method is as follows:
l k indicating the link length, v, of the link k k Representing the free flow velocity of the link k;
2) impedance function of water transport
Reference to a BPR function for road transport;
3) railway transit impedance function
The impedance function of rail transport is linear, as shown by the following equation:
wherein q is k Representing the flow of goods on road section k; f k Representing the capacity of the section k;
in summary, the objective function is as follows:
in S02, the constraint conditions include three of formula (7), formula (8), and formula (9):
wherein the content of the first and second substances,
the flow rate on the kth path between r and s is expressed, K belongs to K, and the constraint condition of the formula (7) expresses the arrival of the containers and the container demand q r Equal; the constraint condition of equation (8) indicates that the container generation quantity is less than the port capacity q s (ii) a The constraint condition of equation (9) represents the road section freight volume q k Is less than the bearing capacity F of the road section k Wherein the carrying capacity F k Specifically, the remaining capacity of the container on the road section, that is, the occupied quantity of other vehicles on the road section and the occupied quantity of container transportation need to be planed, is calculated as follows:
in the formula, Q k Is the designed capacity of the road segment k,
is the occupancy of other vehicles on the road segment k,
is the container traffic occupancy on road segment k.
In S03, the incremental allocation method specifically includes:
s030: preprocessing, namely allocating the special attribute requirements in the overall allocation requirements first, and dividing other conventional requirements into N equal parts, namely
Simultaneously, flow on the road in the road network is initialized to zero, the flow distribution time n is made to be 1, and the initial flow of the road in the road network
Simultaneously inputting road cost matrix t of road network a }; wherein the content of the first and second substances,
distributing the used flow for the node r for one time; q. q.s rs Flow distribution required by cargo source node rTotal flow of (a); n is a counter and indicates the current flow distribution times; alpha is a road network symbol indicator which represents the code number of a specific road in the road network; a is a road set in a road network;
s031: iteratively updates, order
The corresponding cost of each road in the current flow distribution is obtained, obviously
Wherein, t a Representing initial cost corresponding to each road in the road network;
the corresponding cost of each road in the road network is obtained when the flow is distributed for the nth time;
indicates the flow rate configured on the alpha road in the n-1 distribution,
a sensitivity function for road cost of the road network;
s032: incremental distribution, at the current road network cost, will
Distributing the data to a road network to obtain network flow
S033: cumulative road network traffic
Indicates the flow rate allocated on the alpha road in the nth flow allocation,
the specific flow configured on the alpha road in the nth distribution is obtained;
s034: if N is equal to N, iteration is stopped, the current flow is the balance distribution solution, otherwise, N is equal to N +1, and S031 is switched to;
if N is sufficiently large, x a Is sufficiently small because
Relatively fixed, the fixed-phase separation is additive, and the N-step iteration corresponds to
In S03, the Dijkstra algorithm is implemented as follows:
1) firstly, taking one point v 0 as a starting point, initializing dis i, and initializing the value of d i as the distance w 0 i from v 0 to the rest points v i, if the values are directly adjacent, initializing the values to be weight values, otherwise, initializing the values to be infinite;
2) labeling v [0], vis [0] ═ 1, vis is initially initialized to 0;
3) finding the nearest point vk adjacent to v 0, recording the vk point, and recording the distance between vk and v 0 as min;
4) labeling v [ k ], vis [ k ] ═ 1;
5) inquiring and comparing, comparing dis [ j ] with MIN + w [ k ] [ j ], and judging whether v [0] is directly connected with v [ j ] to be short or v [ j ] is connected with v [ k ] to be shorter, namely dis [ j ] is MIN (dis [ j ], MIN + w [ k ] [ j ]);
6) and continuously repeating the step 3) and the step 5) until all the points are found.
The invention has the beneficial effects that: the invention introduces traffic distribution in the traffic field into a port cluster distribution system, considers the influence of road impedance during distribution, and can more truly and comprehensively describe the traffic condition of the port cluster distribution system by matching with various transportation modes, thereby providing more accurate traffic flow information for participants and traffic planners of port cluster abdominal logistics.
Drawings
FIG. 1 is a flow chart of a traffic distribution method of a container collection and distribution system of a port cluster according to the present invention;
FIG. 2 is an abstract view of the harbor relations of the present invention;
FIG. 3 is a flow chart of an incremental assignment algorithm of the present invention;
FIG. 4 is a flow chart of Dijkstra algorithm of the present invention;
FIG. 5 is a schematic diagram of the capacity of the highway and railway line and the container in Shandong province according to the embodiment of the invention;
FIG. 6 is a plot of a region total logistics cost fit function according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating an accumulated cost trend of various aspects of the present invention.
Detailed Description
The present invention is further described with reference to the accompanying drawings, and the following examples are only for clearly illustrating the technical solutions of the present invention, and should not be taken as limiting the scope of the present invention.
As shown in fig. 1, the invention provides a traffic distribution method for a port cluster container collection and distribution system, comprising the following steps:
step one, abstracting an undirected graph containing nodes and edges according to the harbor relations in the harbor cluster container shipping system. The nodes in the undirected graph comprise a source city, a middle city, a road intersection, a transportation mode conversion point and a port; the edge comprises three transportation lines of male, iron and water transportation modes.
And secondly, establishing a traffic distribution model of the port cluster container transportation system, wherein the traffic distribution model is used for minimizing and calculating the sum of direct transportation cost and transfer cost, representing road impedance by a BPR function in the direct transportation cost, converting time in the BPR function into a cost form through transportation time value, and establishing constraint conditions to ensure that the transportation volume and time of each stage in the transportation process meet requirements.
The expression of the traffic distribution model is as follows:
wherein the content of the first and second substances,minC represents the minimum value of the sum of direct transportation cost and transfer cost, R is a container generation place set, S is a container destination port set, K is a set of all paths between a container generation place R and a port S and contains different transportation modes, a road section a is positioned between two nodes, a road section is only one transportation mode, a belongs to A, A is a set of all road sections, B can be any node between R and S, B belongs to B, and B is a set of all intermediate nodes;
is a decision variable, if the road segment a is on the kth road segment between r and s
Otherwise
Is a decision variable, if the goods are transferred in node b between r and s
Otherwise
Is the direct transportation cost for the kth road segment between r and s;
is the cost of transfer in node b between r and s;
in addition, the first and second substrates are,
and
the calculation of (c) is as follows:
wherein the content of the first and second substances,
representing the value of unit transit time, t k Indicating the time of the shipment of the goods, in hours,
representing the flow of goods converted in node b between r and s, f tr The expression represents the transfer rate in transfer, tau represents the transfer coefficient,
represents the time of transfer in node b between r and s;
wherein the road resistance function t k Under different conditions, the method has different forms, in particular:
1) road transport impedance function
Considering the influence of road congestion on the cost, a road impedance factor is added to the cost function. The thesis adopts the relationship between the road section passing time and the road flow proposed by the U.S. federal highway administration, namely a BPR function, which is in the form of:
where α, β are time-cost fit parameters of the BPR function, q k Indicating the flow of goods on section k, F k Representing the capacity of a section k, t free,k The free-stream travel time for link k is represented by the following calculation:
l k indicating the link length, v, of the link k k Representing a section of road kA free stream velocity;
2) impedance function of water transport
At present, the time cost and the corresponding impedance function for researching waterway transportation in the academic world are less, the generalized cost of the waterway transportation has certain elasticity, and particularly on a channelized waterway, the time for waiting for the passing of the brake is increased along with the increase of the requirement of the passing of the brake, so that the waterway transportation and the highway transportation have the characteristics which are relatively similar.
Therefore, the impedance function of the water transportation in the model refers to the BPR function of the road transportation, wherein the values of alpha and beta are selected and calibrated according to the actual situation of a research area on the basis of small-scale experiments.
3) Railway transit impedance function
In the multi-type intermodal transportation, the railway transportation is different from the road transportation and the waterway transportation, the freight transportation capacity is completely determined by a railway train operation diagram and the single-train secondary freight transportation capacity, and the generalized cost has no elasticity. Thus, the impedance function of rail transport is linear, as shown by:
wherein q is k Representing the flow of goods on the road section k; f k Representing the capacity of the section k;
in summary, the objective function is as follows:
in the second step, the constraint conditions include three formulas (7), (8) and (9):
wherein the content of the first and second substances,
the flow rate of the K-th path between r and s (K belongs to K) is expressed, and the constraint condition of the formula (7) expresses the arrival of the containers and the required container quantity q r Equal; the constraint condition of equation (8) indicates that the container generation quantity is less than the port capacity q s (ii) a The constraint condition of equation (9) represents the road section freight volume q k Is less than the bearing capacity F of the road section k Wherein the carrying capacity F k Specifically, the remaining capacity of the container on the road section, that is, the occupied quantity of other vehicles on the road section and the occupied quantity of container transportation need to be planed, the calculation method is as follows:
in the formula, Q k Is the designed capacity of the road segment k,
is the occupancy of other vehicles on the road segment k,
is the container traffic occupancy on road segment k.
And step three, solving the algorithm of the traffic distribution model of the port cluster container distribution system, wherein the generalized cost and the flow of each road section have an obvious feedback function, so that when the model is gradually solved, the iteration result of the network node in the previous step can influence the initial cost road network in the next step, and the incremental distribution method is adopted to gradually distribute and solve the road network flow in order to reduce the human error caused by the flow distribution sequence.
In the step-by-step flow distribution, an initial cost table of a road network is given through a generalized cost model, in each increment of an increment distribution method, the increment flow of the road network nodes is distributed according to a given sequence and the minimum cost principle according to the cost table, and a Dijkstra algorithm is adopted in the distribution.
As shown in fig. 3, the incremental allocation method comprises the following specific steps:
s030: preprocessing, namely allocating the special attribute requirements in the overall allocation requirements first, and dividing other conventional requirements into N equal parts, namely
Simultaneously, flow on the road in the road network is initialized to zero, the flow distribution time n is made to be 1, and the initial flow of the road in the road network
Simultaneously inputting road cost matrix t of road network a And (c) the step of (c) in which,
distributing the used flow for the node r for one time; q. q.s rs The total flow rate of the required distribution for the cargo source node r;
the flow rate configured on the alpha road in the nth flow distribution is shown; n is a counter indicating the current flow distribution times; alpha is a road network symbol indicator which represents the code number of a specific road in the road network; a is a road set in a road network)
S031: iteratively updates, order
The corresponding cost of each road in the current flow distribution is obtained, obviously
Wherein, t a Representing initial cost corresponding to each road in the road network;
distributing each road in road network for nth timeThe cost corresponding to the road;
is a sensitivity function of road cost of the road network. )
S032: incremental distribution, at the current road network cost, will
Distributing the data to a road network to obtain network flow
S033: cumulative road network traffic
S034: if N is N, the iteration is stopped, the current flow is the balance distribution solution, otherwise, N is N +1, and S031 is carried out.
If N is sufficiently large, x a Is sufficiently small because
Relatively fixed, the fixed-phase separation is additive, and the N-step iteration corresponds to
As shown in fig. 4, Dijkstra algorithm is implemented as follows:
1) firstly, taking one point v 0 as a starting point, initializing dis i, and initializing the value of d i as the distance w 0 i from v 0 to the rest points v i, if the values are directly adjacent, initializing the values to be weight values, otherwise, initializing the values to be infinite;
2) labeling v [0], vis [0] ═ 1, vis is initially initialized to 0;
3) finding the nearest point vk adjacent to v 0, recording the vk point, and recording the distance between vk and v 0 as min;
4) labeling v [ k ], vis [ k ] ═ 1;
5) inquiring and comparing, comparing dis [ j ] with MIN + w [ k ] [ j ], and judging whether v [ j ] is directly connected with v [0] and is short or is connected with v [ j ] through v [ k ] and is shorter, namely dis [ j ] is MIN (dis [ j ], MIN + w [ k ] [ j ]);
6) and continuously repeating the step 3) and the step 5) until all the points are found.
The traffic distribution method of the port cluster container collecting and distributing system provided by the invention is implemented by taking a comprehensive transport network of landcontainers in Shandong province as an example, and an optimized result is obtained.
Analyzing the logistics relationship between a port and a belly city, and constructing a port city relationship abstract drawing
As shown in fig. 2, the container generated by the container generation node selects a geographically closest and connectable port as a destination port, and there are a plurality of roads and railways to choose from, and when the road traffic is low, a terminal channel can be chosen by using the minimum cost flow as the shortest path selection criterion. However, when the flow rate is gradually increased and the cost and the time are greatly increased due to the congestion of some roads, the selection is biased to a channel with smaller congestion degree and lower cost, and in the port cluster distribution system, the channel may be one of a road and a railway or a combination of two transportation modes. Thus, each increase in flow affects the next selection in anticipation of a win-win combination of time and cost. For the harbour group on the belly, the spontaneous selection of the more unobstructed road can equalize the traffic trend in the whole area.
The port and city relation of container transportation is abstracted into a directed network G (N, A), wherein N is a freight node set, A is a freight road section set, R is a container generation city set, and S is a container distribution port set. Note q k The freight volume k on the road section k belongs to A when the land transportation mode is adopted, and the cost function of the road section k is t k (q k ). Let t be k (q k ) Is a non-negative, non-decreasing convex function.
Second, simulation result
The quantity of containers exported in 2017 by Qingdao customs (17 places and cities in province) is distributed in an increment mode, the number of times is 10, and the total quantity of the containers is distributed in each time by 10%.
The regional total logistics cost after each container flow allocation is analyzed and the cost function follows a quadratic distribution as shown in fig. 7. When less than 70% of the total amount of the container containers in the container terminal is distributed to the existing network, the logistics cost rises slowly, and the container terminal system adapts to the container flow at the stage, so that the congestion condition cannot be caused. But starting from the total amount allocated of 80%, the total logistics cost of the area increases dramatically, which is a result of the broadening effect of the road impedance in the cost function, namely: when container traffic causes a certain degree of congestion to the road network, the cost of the traffic increases in the form of a higher power. The method shows that the existing traffic infrastructure in Shandong province bears the transportation volume within 80 percent of the shipping volume of the port cluster container economically and reasonably, and obvious scale uneconomic performance is shown when the transportation volume exceeds the shipping volume. The above research conclusion is also consistent with the investigation data that the road network lateral congestion degree of Shandong province is 1.09, and the transport volume of the containers borne by the highway and railway transportation accounts for 80%, and the accuracy of the model is verified.
It can be seen from fig. 6 that the cost function of the port box follows the following distribution:
y＝2433x 2 -6256.8x+21537
analyzing the distribution process, finding that the container throughput of the Qingdao harbor occupies the dominant position in the coastal three harbors, the container generation field is mainly concentrated in the south of China and the surrounding areas of the south of China, and the original rubber line and the new stone line in the network channel bear the most containers and have the most serious congestion. Therefore, the research combines the Shandong province to add east-west channel in the railway building project, namely the Delong-Nicotiana railway (blue railway line in figure 5) and add a virtual middle railway line (purple railway line in figure 5) between the rubber line and the new stone line for simulation. The total cost of the new stream is shown in table 1.
TABLE 1
The cumulative cost of the ten dispensed streams in the table decreases sequentially from left to right. The increase of container transportation function in the constructed Delong tobacco railway can reduce the total logistics cost by 2.24%, the virtual construction and operation of the middle railway line can reduce the logistics cost of the container in the harbor by 4.18%, and if the two railway lines are simultaneously put into the operation of the container in the harbor, the logistics cost can be obviously reduced by 11.69%. As shown in fig. 7.
Figure 7 represents visually the variation of increasing the railway port collecting capacity and the total logistics cost: before the seventh distribution, the whole road network is in a healthier state, and the total logistics cost of each distribution scheme is slowly increased (the cost of a single box is not greatly changed), so that the map mainly selects a 70-100% interval analysis in which the logistics cost of a region is rapidly changed. As shown in the figure, the contribution of adding a virtual 'middle railway line' to reducing the regional logistics cost is far greater than the increase of the passing capacity of the container of the delong railway under construction, on one hand, the main service range of the delong railway is the north area of the Shandong province, and the delong railway is not consistently taken as the middle city of the mountain province land-sea linkage transport capacity demand core area; on the other hand, the container handling capacity of the Qingdao harbor is higher than that of other harbors in the whole province, and the actual collection and distribution requirements of Shandong province can be better met by taking the Qingdao city as a terminal point for the middle railway line. Therefore, for the land-sea linkage under the container view angle, the existing railway construction in Shandong province cannot meet the requirements, and the related research of 'middle railway lines' is proposed to be developed.
The foregoing is only a preferred embodiment of the present invention and numerous modifications and alterations may be made thereto without departing from the principles of the invention and these modifications and alterations should be seen as within the scope of the invention.
Claims (4)
1. A port cluster container collecting and distributing system traffic distribution method is characterized in that: the method comprises the following steps:
s01, abstracting an undirected graph containing nodes and edges according to the harbor relations in the harbor cluster container centralized distribution system;
s02, establishing a traffic distribution model of the port cluster container distribution system, wherein the traffic distribution model is used for minimizing and calculating the sum of direct transportation cost and transfer cost, representing road impedance by a BPR function in the direct transportation cost, converting time in the BPR function into a cost form through transportation time value, and establishing a constraint condition to ensure that the transportation volume and time of each stage in the transportation process meet requirements;
the expression of the traffic distribution model is as follows:
wherein minC represents the minimum value of the sum of direct transportation cost and transfer cost; r is a container generation place set, S is a container destination port set, K is a set of all paths between a container generation place R and a port S and comprises different transportation modes, a road section a is positioned between two nodes, the road section a is only one transportation mode, a belongs to A, A is a set of all road sections, B can be any node between R and S, B belongs to B, and B is a set of all intermediate nodes;
is a decision variable, if the road segment a is on the kth road segment between r and s
Otherwise
Is a decision variable, if the goods are transferred in node b between r and s
Otherwise
Is the direct transportation cost for the kth road segment between r and s;
is the cost of transfer in node b between r and s;
in addition, the first and second substrates are,
and
the calculation method of (c) is as follows:
wherein, the first and the second end of the pipe are connected with each other,
representing the value of unit transit time, t k Indicating the time of the shipment of the goods, in hours,
representing the flow of transshipment in node b between r and s, f tr Represents the transfer rate in transfer, tau represents the transfer coefficient,
represents the time of transfer in node b between r and s;
wherein the road resistance function t k Under different conditions, the method has different forms, in particular:
1) road transport impedance function
A BPR function is used, of the form:
where α, β are time-cost fit parameters of the BPR function, q k Indicating the flow of goods on section k, F k Representing the capacity of a section k, t free,k The free-stream travel time for link k is represented by the following calculation:
l k indicating the link length, v, of the link k k Representing the free flow velocity of the link k;
2) impedance function of water transport
Reference to a BPR function for road transport;
3) railway transit impedance function
The impedance function of rail transport is linear, as shown by the following equation:
wherein q is k Representing the flow of goods on road section k; f k Representing the capacity of the section k;
in summary, the objective function is as follows:
s03, stepwise distributing and solving the road network flow by adopting an incremental distribution method, giving an initial cost table of the road network through a generalized cost model in stepwise flow distribution, distributing the incremental flow of road network nodes according to a given sequence in each increment of the incremental distribution method according to the cost table by a minimum cost principle, and adopting a Dijkstra algorithm in distribution;
the increment distribution method comprises the following specific steps:
s030: preprocessing, namely allocating the special attribute requirements in the overall allocation requirements first, and dividing other conventional requirements into N equal parts, namely
Simultaneously, the flow on the road in the road network is initialized to zero, the flow distribution times n is equal to 1, and the initial flow of the road in the road network
Simultaneously inputting road cost matrix t of road network a }; wherein the content of the first and second substances,
distributing the used flow for the node r for one time; q. q.s rs The total flow rate of the required distribution for the cargo source node r; n is a counter and indicates the current flow distribution times; alpha is a road network symbol indicator which represents the code number of a specific road in the road network; a is a road set in a road network;
s031: iteratively updates, order
The corresponding cost of each road in the current flow distribution is obtained, obviously
Wherein, t a Representing initial cost corresponding to each road in the road network;
the corresponding cost of each road in the road network is obtained when the flow is distributed for the nth time;
indicates the flow rate configured on the alpha road in the n-1 distribution,
for road networkA sensitivity function of road cost;
s032: incremental distribution, at the current road network cost, will
Distributing the traffic to a road network to obtain network flow
S033: cumulative road network traffic
Indicates the flow rate allocated on the alpha road in the nth flow allocation,
the specific flow configured on the alpha road in the nth distribution is obtained;
s034: if N is equal to N, iteration is stopped, the current flow is the balance distribution solution, otherwise, N is equal to N +1, and S031 is switched to;
if N is sufficiently large, x a Is sufficiently small because
Relatively fixed, the fixed-phase separation is additive, and the N-step iteration corresponds to
2. The traffic distribution method of the port cluster container collection and distribution system according to claim 1, wherein: in S01, the nodes in the undirected graph comprise a source city, a middle city, a road intersection, a transportation mode conversion point and a port; the edge comprises three transportation lines of male, iron and water transportation modes.
3. The traffic distribution method of the port cluster container collection and distribution system according to claim 1, wherein: in S02, the constraint conditions include three of formula (7), formula (8), and formula (9):
wherein the content of the first and second substances,
the flow rate on the kth path between r and s is expressed, K belongs to K, and the constraint condition of the formula (7) expresses the arrival of the containers and the container demand q r Equal; the constraint condition of equation (8) indicates that the container generation quantity is less than the port capacity q s (ii) a The constraint condition of equation (9) represents the road section freight volume q k Less than the carrying capacity F of the section k Wherein the carrying capacity F k Specifically, the remaining capacity of the container on the road section, that is, the occupied quantity of other vehicles on the road section and the occupied quantity of container transportation need to be planed, is calculated as follows:
in the formula, Q k Is the designed capacity of the road segment k,
is the occupancy of other vehicles on the road segment k,
is the container traffic occupancy on road segment k.
4. The traffic distribution method of the port cluster container collection and distribution system according to claim 1, wherein: in S03, the Dijkstra algorithm is implemented as follows:
1) firstly, taking one point v 0 as a starting point, initializing dis i, and initializing the value of d i as the distance w 0 i from v 0 to the rest points v i, if the values are directly adjacent, initializing the values to be weight values, otherwise, initializing the values to be infinite;
2) labeling v [0], vis [0] ═ 1, vis is initially initialized to 0;
3) finding the nearest point vk adjacent to v 0, recording the vk point, and recording the distance between vk and v 0 as min;
4) labeling v [ k ], vis [ k ] ═ 1;
5) inquiring and comparing, comparing dis [ j ] with MIN + w [ k ] [ j ], and judging whether v [ j ] is directly connected with v [0] and is short or is connected with v [ j ] through v [ k ] and is shorter, namely dis [ j ] is MIN (dis [ j ], MIN + w [ k ] [ j ]);
6) and continuously repeating the step 3) and the step 5) until all the points are found.
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