CN116562483A - Port area set card group path optimization method and computer readable medium - Google Patents

Port area set card group path optimization method and computer readable medium Download PDF

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CN116562483A
CN116562483A CN202310470096.7A CN202310470096A CN116562483A CN 116562483 A CN116562483 A CN 116562483A CN 202310470096 A CN202310470096 A CN 202310470096A CN 116562483 A CN116562483 A CN 116562483A
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road
node
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刘永悦
严新平
贺宜
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Wuhan University of Technology WUT
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Abstract

The invention discloses a harbor area set card group path optimization method and a computer readable medium. The method comprises the steps of constructing a harbor road network model and obtaining traffic flow information of the harbor road network; acquiring the weighted lengths of a starting node, a target node and a road section of a to-be-decided set card driving path; based on the weighted lengths of the starting node, the target node and the road section of the driving path of the set card to be decided, an improved Di Jie Style algorithm is adopted to obtain an optimal path; the improved Dijiesla algorithm is characterized in that the searching mode and the weight of the Dijiesla algorithm are improved; the improved searching mode is as follows: bidirectional sector dynamic searching; the improved weight is as follows: the weighted length of the road segment. The Di Jie St algorithm is improved by utilizing the searching mode and the weight of the algorithm, so that the algorithm has instantaneity, the influence of real-time road conditions on the travel path decision of the set card is considered, a better path decision scheme can be provided for the set card, and the transportation efficiency of the set card and the harbor district operation level are improved.

Description

Port area set card group path optimization method and computer readable medium
Technical Field
The invention relates to the technical field of traffic path planning in intelligent traffic, in particular to a harbor area set card group path optimization method and a computer readable medium.
Background
The dijkstra algorithm is a common algorithm for solving the shortest path in graph theory proposed by the netherlands computer scientist e.w. dijkstra, and is the most complete and most extensive algorithm for solving the shortest path problem at present. However, when the dijkstra algorithm is used to plan the port area set card driving path, only the shortest path problem is considered, and the influence caused by the real-time road condition of the port area is not considered, which may cause that a large number of vehicles simultaneously select the same shortest path, thereby causing congestion phenomenon and reducing the utilization rate of the port area road and the transportation efficiency of the set card. The traditional Dijiestra algorithm also has blindness in the search direction, the search range is larger, the search efficiency is lower, the algorithm lacks real-time performance, and the dynamic search function is not provided.
Disclosure of Invention
In order to solve the above problems, the present invention provides a harbor set card group path optimization method and a computer readable medium.
The technical scheme of the method is a harbor area set card group path optimization method, which specifically comprises the following steps:
step 1: combining map distribution information of the harbor road network, obtaining each intersection of the harbor road network and a road section between the two intersections, defining the weighted length of the road section, constructing a harbor road network model, and obtaining traffic flow information of the harbor road network;
step 2: acquiring a starting node and a target node of a driving path of a set card to be decided and a weighted length of each road section;
step 3: and obtaining an optimal path by adopting an improved Di Jie Style algorithm based on the starting node and the target node of the driving path of the set card to be determined and the weighted length of each road section.
Preferably, the constructing a port road network model in the step 1 specifically includes:
defining each intersection of the harbor area road network as each node of the harbor area road network model, defining a road section between two intersections as a road section connection state between two nodes of the harbor area road network model, and defining the weighted length of the road section between the two intersections as the road section weight between two connecting nodes of the harbor area road network model;
the harbor road network model is expressed as:
R＝(V,E,W)
V＝{node 1 ,node 2 ,..,node n }
E＝{e x,y |x∈[1,n]，y∈[1,n]，x≠y}
W＝{w x,y |x∈[1,n]，y∈[1,n]，x≠y}
wherein R represents a port road network model; v is node set of harbor district road network model x The method is characterized in that the method is an xth node of the harbor district road network model, and n is the total number of nodes of the harbor district road network model; e is a road section connection state set between two nodes of the harbor district road network model, E x,y Representing the road section connection state between the xth node and the yth node of the harbor district road network model, if e x,y If =1, there is a road section between the x node and the y node of the harbor district road network model, if e x,y =0 is absent; w is a road section weight set between two phase connection points of a harbor district road network model, and W x,y Representing the weight of the road section between the xth node and the yth node of the harbor district road network model, if e x,y W is =0 x,y Absence of;
the weighted length of the road section is obtained by comprehensively considering the actual length of the road section, the traffic flow of the road section and the congestion degree of the road section to calculate and solve;
the obtaining of the traffic flow information of the harbor road network in the step 1 is specifically as follows:
acquiring traffic flow data information of each road section of a harbor region through a harbor region road management center;
preferably, in the step 2, a starting node and a target node of a to-be-decided set card driving path are obtained based on set card transportation operation task information;
the step 2 of obtaining the weighted length of each road section specifically includes the following steps:
step 2.1: obtaining the actual length L of the road section k k Wherein k is more than or equal to 1 and less than or equal to s, and s is the total number of harbor sections;
step 2.2: obtaining time t required by the road segment k for the traffic collection card to pass through the road segment k in a unobstructed state k ：
Wherein t is free,k A free travel time representing road segment k; v k A free flow speed representing a road segment k; q k Road traffic flow representing road segment k; f (F) k Representing the traffic capacity of road section k; alpha is a proportional parameter, beta is an exponential parameter, t k Representing the time required by the traffic segment k;
step 2.3: obtaining a congestion penalty value omega of a road section k in a congestion state k ：
Equally dividing the road section k into i sub-road sections, and selecting the vehicle density of the sub-road section with the highest congestion degree as the congestion penalty value omega of the road section k k ；
Step 2.4: taking the actual length L of a road section, the time t required for a collector card to pass through the road section in a road section unobstructed state and the road section congestion punishment value omega in a road section congestion state as columns, and the actual length L of a kth road section k Time t required for passing through road section of collector card in unobstructed state of kth road section k And a road congestion penalty value ω in a congestion state of the kth road segment k The number of the port road sections is greater than or equal to 1 and less than or equal to s, wherein s is the total number of the port road sections; establishing a decision matrix A:
sequentially carrying out normalization processing on each element in the decision matrix to obtain an attribute value of each element in the decision matrix after normalization:
wherein r is i,j Normalized elements of the ith row and jth column in decision matrix AAttribute value of a (a) i,j For the elements of row i and column j in the decision matrix a,for a in the j th column i,j Minimum value->For a in the j th column i,j I is more than or equal to 1 and less than or equal to s, j is more than or equal to 1 and less than or equal to 3,i, and j is an integer;
step 2.5: according to the actual length L of the road section, the time t required by the collector card to pass the road section in the unobstructed state of the road section and the road section congestion punishment value omega three attributes in the congested state of the road section, a professional decision maker is selected to establish an evaluation group through a Delphi method, and a judgment matrix is constructed according to a (1, 9) nine-scale method, so that the actual length L of the road section, the time t required by the collector card to pass the road section in the unobstructed state of the road section and the road section actual length attribute of the road section congestion punishment value omega road section in the congested state of the road section, the time attribute required by the collector card to pass the road section and the weight corresponding to the road section congestion punishment value attribute are u respectively 1 ,u 2 ,u 3 ；
Step 2.6: calculating the weighted length of each road section by the attribute weight and the attribute value:
W k ＝u 1 r k,1 +u 2 r k,2 +u 3 r k,3
wherein W is k For the weighted length of the kth road section, u 1 ,u 2 ,u 3 ∈(0,1)，r k,1 Normalized road segment actual length attribute value r for the kth road segment k,2 The time attribute value r of the passing road section of the collection card in the unobstructed state of the normalized road section of the kth road section k,3 The attribute value of the road section congestion penalty value is the normalized road section congestion state of the kth road section;
preferably, the step 3 adopts a modified Di Jie Style algorithm to obtain an optimal path, and specifically comprises the following steps:
step 3.1: classifying harbor district road network nodes into traversing node sets D in forward search according to the search direction of an algorithm 1 And traversing node set D in reverse search 2 The method comprises the steps of carrying out a first treatment on the surface of the According to the searching range of the algorithm, the method is divided into a node set H in the sector searching range and a node set Q not in the sector searching range; during algorithm calculation, nodes in the sector search range are divided into a temporary node set R and a dynamic node set U;
step 3.2: initializing various parameters in the improved Di-Jie-St algorithm, and taking the weighted length W of the harbor district road network section as the weight of the improved Di-Jie-St algorithm; acquiring a starting node m and a target node d of a to-be-decided set card path, setting U= { m, d }, is an empty set; judging whether traversing nodes in the harbor district road network model are in a sector search range or not, if so, adding a set H, otherwise, adding a set Q;
step 3.3: finding out nodes connected with the direct edges of the initial node m and the target node d from the set H, adding the nodes into the set R, and deleting the nodes from the set H;
step 3.4: finding out a node c with the minimum improved algorithm weight W of a starting node m or a target node d in the set R, adding the node c into the set H and deleting the node c from the set R;
step 3.5: finding out a node which is directly connected with the node c and is not in the set H, adding the node into the set R, and deleting the node from the set H;
step 3.6: finding out the node with the minimum improved algorithm weight W to the node c in the set R, adding the node into the set H and deleting the node from the set R;
step 3.7: judgment D 1 、D 2 If the intersection of (1)Stopping the search algorithm to finish and outputting the optimal path; whether or notA new round of bi-directional searching is performed until a termination condition is met.
The beneficial effects of the technical scheme are as follows: the invention improves the searching mode and the weight of the algorithm, so that the algorithm has real-time performance and dynamic searching function, considers the influence of real-time road conditions on the path decision, improves the searching efficiency of the algorithm, and can provide a better path decision scheme for the set card.
The invention also provides a computer readable medium storing a computer program for execution by an electronic device, which when run on the electronic device performs the steps of the harbor deck group card path optimization method.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides an improved Di Jie St La algorithm which can be used for the optimal path decision of a port set card group, and aims to solve the problems that the traditional Di Jie St La algorithm only considers the shortest path when planning the port set card driving path, ignores the influence of the port road conditions such as the road traffic and the crowding degree on the path planning, and has large searching range, low searching efficiency and lack of real-time performance. Starting from the searching mode and the weight of the Di-Jie-Tesla algorithm, the Di-Jie-Tesla algorithm is improved by utilizing the bidirectional sector dynamic searching and the weighted length of the road section, a better path decision scheme is provided for the set card, and the transport efficiency of the set card and the utilization rate of the harbor road are improved.
Drawings
Fig. 1: the method of the embodiment of the invention is a flow chart;
fig. 2: the method for solving the problem is a flow chart.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The following describes a method for optimizing a port area set card group path according to a specific embodiment of the invention with reference to fig. 1-2, wherein the method comprises the following steps:
the flow of the method in the embodiment of the invention is shown in the figure 1, and comprises the following steps:
step 1: combining map distribution information of the harbor road network, obtaining each intersection of the harbor road network and a road section between the two intersections, defining the weighted length of the road section, constructing a harbor road network model, and obtaining traffic flow information of the harbor road network;
the harbor district road network model is constructed in the step 1, and the method specifically comprises the following steps:
defining each intersection of the harbor area road network as each node of the harbor area road network model, defining a road section between two intersections as a road section connection state between two nodes of the harbor area road network model, and defining the weighted length of the road section between the two intersections as the road section weight between two connecting nodes of the harbor area road network model;
the harbor road network model is expressed as:
R＝(V,E,W)
V＝{node 1 ,node 2 ,..,node n }
E＝{e x,y |x∈[1,n]，y∈[1,n]，x≠y}
W＝{w x,y |x∈[1,n]，y∈[1,n]，x≠y}
wherein R represents a port road network model; v is node set of harbor district road network model x The method is characterized in that the method is an xth node of the harbor district road network model, and n is the total number of nodes of the harbor district road network model; e is a road section connection state set between two nodes of the harbor district road network model, E x,y Representing the road section connection state between the xth node and the yth node of the harbor district road network model, if e x,y If =1, there is a road section between the x node and the y node of the harbor district road network model, if e x,y =0 is absent; w is a road section weight set between two phase connection points of a harbor district road network model, and W x,y Representing the weight of the road section between the xth node and the yth node of the harbor district road network model, if e x,y W is =0 x,y Absence of;
the weighted length of the road section is obtained by comprehensively considering the actual length of the road section, the traffic flow of the road section and the congestion degree of the road section to calculate and solve;
the obtaining of the traffic flow information of the harbor road network in the step 1 is specifically as follows:
acquiring traffic flow data information of each road section of a harbor region through a harbor region road management center;
step 2: acquiring a starting node and a target node of a driving path of a set card to be decided and a weighted length of each road section;
step 2, acquiring a starting node and a target node of a to-be-decided set card driving path based on set card transportation operation task information;
the step 2 of obtaining the weighted length of each road section specifically includes the following steps:
step 2.1: obtaining the actual length L of the road section k k Wherein k is more than or equal to 1 and less than or equal to s, and s is the total number of harbor sections;
step 2.2: obtaining time t required by the road segment k for the traffic collection card to pass through the road segment k in a unobstructed state k ：
Wherein t is free,k A free travel time representing road segment k; v k A free flow speed representing a road segment k; q k Road traffic flow representing road segment k; f (F) k Representing the traffic capacity of road section k; alpha is a proportional parameter, beta is an exponential parameter, t k Representing the time required by the traffic segment k;
step 2.3: obtaining a congestion penalty value omega of a road section k in a congestion state k ：
Equally dividing the road section k into i sub-road sections, and selecting the vehicle density of the sub-road section with the highest congestion degree as the road section kCongestion penalty value omega k ；
Step 2.4: taking the actual length L of a road section, the time t required for a collector card to pass through the road section in a road section unobstructed state and the road section congestion punishment value omega in a road section congestion state as columns, and the actual length L of a kth road section k Time t required for passing through road section of collector card in unobstructed state of kth road section k And a road congestion penalty value ω in a congestion state of the kth road segment k The number of the port road sections is greater than or equal to 1 and less than or equal to s, wherein s is the total number of the port road sections; establishing a decision matrix A:
sequentially carrying out normalization processing on each element in the decision matrix to obtain an attribute value of each element in the decision matrix after normalization:
wherein r is i,j Normalized attribute value, a, of element in ith row and jth column in decision matrix A i,j For the elements of row i and column j in the decision matrix a,for a in the j th column i,j Minimum value->For a in the j th column i,j I is more than or equal to 1 and less than or equal to s, j is more than or equal to 1 and less than or equal to 3,i, and j is an integer;
step 2.5: according to the actual length L of the road section, the time t required for the collector card to pass the road section in the unobstructed state of the road section and the road section congestion punishment value omega in the congested state of the road section, a professional decision-making person is selected to establish an evaluation group through a Delphi method, and a judgment matrix is constructed according to the nine-scale method (1, 9), so that the actual length L of the road section, the time t required for the collector card to pass the road section in the unobstructed state of the road section and the road section congestion punishment value omega in the congested state of the road section are obtainedThe degree attribute, the time attribute required by the collector card to pass through the road section and the weight corresponding to the road section congestion punishment value attribute are u respectively 1 ,u 2 ,u 3 ；
Step 2.6: calculating the weighted length of each road section by the attribute weight and the attribute value:
W k ＝u 1 r k,1 +u 2 r k,2 +u 3 r k,3
wherein W is k For the weighted length of the kth road section, u 1 ,u 2 ,u 3 ∈(0,1)，r k,1 Normalized road segment actual length attribute value r for the kth road segment k,2 The time attribute value r of the passing road section of the collection card in the unobstructed state of the normalized road section of the kth road section k,3 The attribute value of the road section congestion penalty value is the normalized road section congestion state of the kth road section;
step 3: based on the initial node and the target node of the driving path of the set card to be decided and the weighted length of each road section, an improved Di Jie Style algorithm is adopted to obtain an optimal path;
as shown in fig. 2, the method for obtaining the optimal path by adopting the modified dijkstra algorithm based on the starting node and the destination node of the to-be-determined set card driving path and the weighted length of each road section specifically comprises the following steps:
step 3.1: classifying harbor district road network nodes into traversing node sets D in forward search according to the search direction of an algorithm 1 And traversing node set D in reverse search 2 The method comprises the steps of carrying out a first treatment on the surface of the According to the searching range of the algorithm, the method is divided into a node set H in the sector searching range and a node set Q not in the sector searching range; during algorithm calculation, nodes in the sector search range are divided into a temporary node set R and a dynamic node set U;
step 3.2: initializing various parameters in the improved Di-Jie-St algorithm, and taking the weighted length W of the harbor district road network section as the weight of the improved Di-Jie-St algorithm; get the start of waiting for decision to collect the card routeThe initial node m and the target node d are set to be U= { m, d }, is an empty set; judging whether traversing nodes in the harbor district road network model are in a sector search range or not, if so, adding a set H, otherwise, adding a set Q;
step 3.3: finding out nodes connected with the direct edges of the initial node m and the target node d from the set H, adding the nodes into the set R, and deleting the nodes from the set H;
step 3.4: finding out a node c with the minimum improved algorithm weight W of a starting node m or a target node d in the set R, adding the node c into the set H and deleting the node c from the set R;
step 3.5: finding out a node which is directly connected with the node c and is not in the set H, adding the node into the set R, and deleting the node from the set H;
step 3.6: finding out the node with the minimum improved algorithm weight W to the node c in the set R, adding the node into the set H and deleting the node from the set R;
step 3.7: judgment D 1 、D 2 If the intersection of (1)Stopping the search algorithm to finish and outputting the optimal path; otherwise, a new round of bi-directional searching is performed until the termination condition is met.
Particular embodiments of the present invention also provide a computer readable medium.
The computer readable medium is a server workstation;
the server workstation stores a computer program executed by the electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the harbor area set card group path optimization method.
It should be understood that parts of the specification not specifically set forth herein are all prior art.
It should be understood that the foregoing description of the preferred embodiments is not intended to limit the scope of the invention, but rather to limit the scope of the claims, and that those skilled in the art can make substitutions or modifications without departing from the scope of the invention as set forth in the appended claims.

Claims (6)

1. The harbor district set card group path optimization method is characterized by comprising the following steps:
step 1: combining map distribution information of the harbor road network, obtaining each intersection of the harbor road network and a road section between the two intersections, defining the weighted length of the road section, constructing a harbor road network model, and obtaining traffic flow information of the harbor road network;
step 2: acquiring a starting node and a target node of a driving path of a set card to be decided and a weighted length of each road section;
step 3: and obtaining an optimal path by adopting an improved Di Jie Style algorithm based on the starting node and the target node of the driving path of the set card to be determined and the weighted length of each road section.
2. The harbor deck group path optimization method according to claim 1, wherein:
the harbor district road network model is constructed in the step 1, and the method specifically comprises the following steps:
defining each intersection of the harbor area road network as each node of the harbor area road network model, defining a road section between two intersections as a road section connection state between two nodes of the harbor area road network model, and defining the weighted length of the road section between the two intersections as the road section weight between two connecting nodes of the harbor area road network model;
the harbor road network model is expressed as:
R＝(V,E,W)
V＝{node 1 ,node 2 ,..,node n }
E＝{e x,y |x∈[1,n]，y∈[1,n]，x≠y}
W＝{w x,y |x∈[1,n]，y∈[1,n]，x≠y}
wherein R represents a port road network model; v is node set of harbor district road network model x The method is characterized in that the method is an xth node of the harbor district road network model, and n is the total number of nodes of the harbor district road network model; e is a road section connection state set between two nodes of the harbor district road network model, E x,y Representing the road section connection state between the xth node and the yth node of the harbor district road network model, if e x,y If =1, there is a road section between the x node and the y node of the harbor district road network model, if e x,y =0 is absent; w is a road section weight set between two phase connection points of a harbor district road network model, and W x,y Representing the weight of the road section between the xth node and the yth node of the harbor district road network model, if e x,y W is =0 x,y Absence of;
the weighted length of the road section is obtained by comprehensively considering the actual length of the road section, the traffic flow of the road section and the congestion degree of the road section to calculate and solve;
the obtaining of the traffic flow information of the harbor road network in the step 1 is specifically as follows:
and obtaining the traffic flow data information of each road section of the harbor region through a harbor region road management center.
3. The harbor deck group path optimization method according to claim 2, wherein:
and step 2, acquiring an initial node and a target node of a driving path of the set card to be decided, wherein the initial node and the target node are as follows:
and acquiring an initial node and a target node of the travel path of the set card to be decided based on the set card transportation operation task information.
4. A harbor deck card population route optimization method according to claim 3, wherein:
and step 2, acquiring the weighted length of each road section, wherein the specific steps are as follows:
step 2.1: obtaining the actual length L of the road section k k Wherein, k is more than or equal to 1 and less than or equal to s, s isTotal number of harbor sections;
step 2.2: obtaining time t required by the road segment k for the traffic collection card to pass through the road segment k in a unobstructed state k ：
Wherein t is free,k A free travel time representing road segment k; v k A free flow speed representing a road segment k; q k Road traffic flow representing road segment k; f (F) k Representing the traffic capacity of road section k; alpha is a proportional parameter, beta is an exponential parameter, t k Representing the time required by the traffic segment k;
step 2.3: obtaining a congestion penalty value omega of a road section k in a congestion state k ：
Equally dividing the road section k into i sub-road sections, and selecting the vehicle density of the sub-road section with the highest congestion degree as the congestion penalty value omega of the road section k k ；
Step 2.4: taking the actual length L of a road section, the time t required for a collector card to pass through the road section in a road section unobstructed state and the road section congestion punishment value omega in a road section congestion state as columns, and the actual length L of a kth road section k Time t required for passing through road section of collector card in unobstructed state of kth road section k And a road congestion penalty value ω in a congestion state of the kth road segment k The number of the port road sections is greater than or equal to 1 and less than or equal to s, wherein s is the total number of the port road sections; establishing a decision matrix A:
sequentially carrying out normalization processing on each element in the decision matrix to obtain an attribute value of each element in the decision matrix after normalization:
wherein r is i,j Normalized attribute value, a, of element in ith row and jth column in decision matrix A i,j For the elements of row i and column j in the decision matrix a,for a in the j th column i,j Minimum value->For a in the j th column i,j I is more than or equal to 1 and less than or equal to s, j is more than or equal to 1 and less than or equal to 3,i, and j is an integer;
step 2.5: according to the actual length L of the road section, the time t required by the collector card to pass the road section in the unobstructed state of the road section and the road section congestion punishment value omega three attributes in the congested state of the road section, a professional decision maker is selected to establish an evaluation group through a Delphi method, and a judgment matrix is constructed according to a (1, 9) nine-scale method, so that the actual length L of the road section, the time t required by the collector card to pass the road section in the unobstructed state of the road section and the road section actual length attribute of the road section congestion punishment value omega road section in the congested state of the road section, the time attribute required by the collector card to pass the road section and the weight corresponding to the road section congestion punishment value attribute are u respectively 1 ,u 2 ,u 3 ；
Step 2.6: calculating the weighted length of each road section by the attribute weight and the attribute value:
W k ＝u 1 r k,1 +u 2 r k,2 +u 3 r k,3
wherein W is k For the weighted length of the kth road section, u 1 ,u 2 ,u 3 ∈(0,1)，r k,1 Normalized road segment actual length attribute value r for the kth road segment k,2 Required by the collection card to pass through the road section in the unobstructed state of the normalized road section of the kth road sectionTime attribute value, r k,3 And the attribute value is the attribute value of the road section congestion penalty value under the normalized road section congestion state of the kth road section.
5. The harbor deck group path optimization method according to claim 4, wherein:
the step 3 of obtaining the optimal path by adopting the improved dijkstra algorithm specifically comprises the following steps:
step 3.1: classifying harbor district road network nodes into traversing node sets D in forward search according to the search direction of an algorithm 1 And traversing node set D in reverse search 2 The method comprises the steps of carrying out a first treatment on the surface of the According to the searching range of the algorithm, the method is divided into a node set H in the sector searching range and a node set Q not in the sector searching range; during algorithm calculation, nodes in the sector search range are divided into a temporary node set R and a dynamic node set U;
step 3.2: initializing various parameters in the improved Di-Jie-St algorithm, and taking the weighted length W of the harbor district road network section as the weight of the improved Di-Jie-St algorithm; acquiring a starting node m and a target node d of a to-be-decided set card path, setting U= { m, d },is an empty set; judging whether traversing nodes in the harbor district road network model are in a sector search range or not, if so, adding a set H, otherwise, adding a set Q;
step 3.3: finding out nodes connected with the direct edges of the initial node m and the target node d from the set H, adding the nodes into the set R, and deleting the nodes from the set H;
step 3.4: finding out a node c with the minimum improved algorithm weight W of a starting node m or a target node d in the set R, adding the node c into the set H and deleting the node c from the set R;
step 3.5: finding out a node which is directly connected with the node c and is not in the set H, adding the node into the set R, and deleting the node from the set H;
step 3.6: finding out the node with the minimum improved algorithm weight W to the node c in the set R, adding the node into the set H and deleting the node from the set R;
step 3.7: judgment D 1 、D 2 If the intersection of (1)Stopping the search algorithm to finish and outputting the optimal path; otherwise, a new round of bi-directional searching is performed until the termination condition is met.
6. A computer readable medium, characterized in that it stores a computer program for execution by an electronic device, which computer program, when run on the electronic device, causes the electronic device to perform the steps of the method according to any one of claims 1-5.
CN202310470096.7A 2023-04-27 2023-04-27 Port area set card group path optimization method and computer readable medium Pending CN116562483A (en)

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