CN113343400A - Cooperative layout optimization method and system for urban group comprehensive passenger transport hub - Google Patents
Cooperative layout optimization method and system for urban group comprehensive passenger transport hub Download PDFInfo
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Abstract
The invention relates to a cooperative layout optimization method and system for an urban group comprehensive passenger transport hub. The method comprises the following steps: s1: selecting a target urban group area, and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model; s2: acquiring optimization parameter data of each pivot point in the alternative pivot point set, and inputting an urban group comprehensive passenger transport pivot point layout optimization model, wherein the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on the transfer times among the pivot points and the transportation mode; s3: and solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme. The invention provides decision basis for the integrated construction of the comprehensive passenger transport hub in the urban group, the enhancement of regional linkage capacity and the construction of a highly developed multi-mode integrated comprehensive three-dimensional traffic network in the urban group.
Description
Technical Field
The invention relates to the technical field of site selection layout of an integrated passenger transport hub, in particular to a cooperative layout optimization method and system for an urban group integrated passenger transport hub.
Background
The site selection layout of the comprehensive passenger transport hub is a complex engineering problem, relates to a plurality of key influence factors, and mainly comprises a plurality of indexes such as passenger flow scale in the hub, the aggregation and connection degree of transportation modes in the hub, the coordination degree with the passing capacity of peripheral road networks, the overall planning adaptation degree with each city in a city group and the like, but at present, the hub is qualitatively evaluated according to the indexes, and the measurement standard for quantitatively calculating the overall qualitative index is lacked. In addition, the urban group coverage area is large, the number of hub nodes is large, and screening of alternative hubs is necessary before hub layout optimization.
For the theory that the hub site selection problem is mainly adopted in the hub layout research, the layout methods of the comprehensive passenger transportation hub aiming at the regional level at present mainly comprise three types: a cluster analysis method, a node importance method and a mathematical programming method. The mathematical programming method mainly adopts a classical hub site selection model to perform layout optimization research, and common optimization targets mainly include: the total construction and operation cost is lowest, the total transportation cost is lowest, the travel distribution time is minimum and the like; common constraints mainly include the limitation of the number of hubs, the limitation of capacity, the limitation of service range, and the like. The technology for constructing the optimization model of the site selection layout of the comprehensive passenger transport hub by considering various practical factors and solving the optimization scheme by using the model to obtain the layout optimization scheme of the comprehensive passenger transport hub has wide application, but the overall consideration of simultaneously connecting various transportation modes and multiple transit transportation scenes among hubs in an urban group is lacked when the optimization target is selected, and the synchronous consideration of the connection of the hub service range and the transportation modes is lacked in the constraint condition.
Disclosure of Invention
The invention mainly aims to overcome the defects and shortcomings of the prior art and provides a cooperative layout optimization method and system for an urban group comprehensive passenger transport hub.
According to one aspect of the invention, the invention provides a cooperative layout optimization method for an urban comprehensive passenger transport hub, which comprises the following steps:
s1: selecting a target urban group area, and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model;
s2: acquiring optimization parameter data of each pivot point in the alternative pivot point set, and inputting an urban group comprehensive passenger transport pivot point layout optimization model, wherein the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on the transfer times among the pivot points and the transportation mode;
s3: and solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
Preferably, the construction of the urban group integrated passenger transport pivot point screening model comprises the following steps:
analyzing influence factors of site selection layout of the comprehensive passenger transport hub, and determining site selection indexes;
constructing a factor set according to the site selection indexes, and determining an evaluation set;
calculating the weight distribution coefficient of each factor set and the evaluation result of each pivot point;
assigning a calculation charm value to the evaluation grade in the evaluation set, wherein the charm value is used for screening pivot points to obtain alternative pivot points;
and (4) charm sequencing is carried out on the charm values from large to small, k front nodes are taken from high to low according to the charm and serve as an alternative point set of the comprehensive passenger transport hub in the region, and k is a positive integer.
Preferably, the site selection index includes:
coordinated matching index w1Demand adaptability index w2And social influence index w3(ii) a Wherein the harmonization matchability index w1Involving a degree of coordination w with the overall plan of the city11Degree of coordination w with various transportation modes12Degree of coordination w with urban road wire network layout13(ii) a The demand adaptability index w2Including pivot service radiation range w21Hub construction scale adaptability w22Future development reserved space w of hub23(ii) a The social influence index w3Including the degree of influence w on the load of the road network around the hub31Degree of influence w on urban population and industrial layout32Influence degree w on urban environment33。
Preferably, the constructing a factor set according to the site selection index and determining an evaluation set includes:
dividing the site selection index to obtain four factor sets W ═ W1，w2，w3}，w1＝{w11,w12,w13},w2＝{w21,w22,w23},w3＝{w31,w32,w33Each factor set contains three indexes; the evaluation set is { excellent, good, general, poor }.
Preferably, a judgment matrix and an evaluation matrix of the factor set are constructed to obtain evaluation results of each site selection index; and performing score assignment on the evaluation grades in the evaluation set, multiplying the evaluation grade scores and the evaluation results of the corresponding grades, and summing to obtain the charm value of the pivot point.
Preferably, the constructing of the urban group integrated passenger transport hub layout optimization model includes:
the passenger station is divided into an integrated passenger transport pivot point and a non-integrated passenger transport pivot point, and the transport modes between the pivot points are divided into a direct transport mode and an indirect transport mode;
and setting a target function, decision variables and constraint conditions of the model, and constructing the urban group comprehensive passenger transport pivot point layout optimization model based on the transfer times among the pivot points and the transportation mode.
Preferably, the objective function comprises:
the method comprises the following steps of minimizing a first objective function by comprehensively considering the total operation cost of the passenger terminal, minimizing a second objective function by comprehensively considering the secondary transfer among terminals and the total transportation cost selected by different transportation modes, and minimizing a third objective function by comprehensively considering the secondary transfer among terminals and the transfer transportation time selected by different transportation modes.
Preferably, the setting of the decision variables comprises:
setting a 0-1 decision variable which represents whether the alternative point in the target area is selected as the integrated passenger transport pivot point or not;
setting a 0-1 decision variable which indicates whether the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport hub or not;
setting a decision variable 0-1 for indicating whether the passenger flow of a certain origin-destination point i-j in the target area is directly transported;
setting a 0-1 decision variable which represents whether a traffic mode h is selected from a starting point i to a comprehensive passenger transport pivot point k when the passenger flow of a certain destination point i-j in a target area is transferred through the comprehensive passenger transport pivot point;
setting a 0-1 decision variable which indicates whether a traffic mode h is selected from a comprehensive passenger transport pivot point k to a comprehensive passenger transport pivot point m when the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point;
and setting a 0-1 decision variable which represents whether the traffic mode h is selected from the comprehensive passenger transport pivot point m to the destination j when the passenger flow of a certain destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point.
Preferably, the constraints of the model include:
the method comprises the following steps of comprehensive passenger transport hub station quantity limitation, transport mode selection limitation, comprehensive passenger transport hub entrance and exit passenger flow conservation limitation, transit passenger flow composition limitation, direct transport passenger flow composition limitation, origin-destination total passenger flow composition limitation, node passenger flow generation amount and passenger flow attraction amount balance limitation, comprehensive passenger transport hub capacity limitation, comprehensive passenger transport hub service range and transport mode selection limitation.
According to another aspect of the present invention, the present invention further provides a cooperative layout optimization system for an urban group integrated passenger transportation hub, the system comprising:
the screening module is used for selecting a target urban group area and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model;
the input module is used for acquiring optimization parameter data of each pivot point in the alternative pivot point set and inputting an urban group comprehensive passenger transport pivot point layout optimization model, and the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on transit times among the pivot points and a transportation mode;
and the optimization module is used for solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
Has the advantages that: according to the invention, through constructing a charm-based urban group comprehensive passenger transport hub alternative point screening model and constructing an urban group comprehensive passenger transport hub collaborative layout optimization model considering the linkage of a secondary transfer scene between hubs and different transportation modes, an optimization scheme of the layout of the urban group comprehensive passenger transport hubs is obtained after solving, and a decision basis is provided for the integrated construction of the urban group comprehensive passenger transport hubs, the regional linkage capacity is enhanced, and a highly developed multi-mode integrated comprehensive three-dimensional transportation network in the urban group is constructed.
The features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of specific embodiments of the invention.
Drawings
FIG. 1 is a flow chart of a method for optimizing the cooperative layout of an urban complex integrated passenger transport hub;
fig. 2 is a schematic diagram of a cooperative layout optimization system of an urban complex integrated passenger transport hub.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Fig. 1 is a flow chart of a cooperative layout optimization method of an urban complex comprehensive passenger transport hub. As shown in fig. 1, the invention provides a cooperative layout optimization method for an urban comprehensive passenger transport hub, which comprises the following steps:
s1: selecting a target urban group area, and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model.
Preferably, the construction of the urban group integrated passenger transport pivot point screening model comprises the following steps:
analyzing influence factors of site selection layout of the comprehensive passenger transport hub, and determining site selection indexes;
constructing a factor set according to the site selection indexes, and determining an evaluation set;
calculating the weight distribution coefficient of each factor set and the evaluation result of each pivot point;
assigning a calculation charm value to the evaluation grade in the evaluation set, wherein the charm value is used for screening pivot points to obtain alternative pivot points;
and (4) charm sequencing is carried out on the charm values from large to small, k front nodes are taken from high to low according to the charm and serve as an alternative point set of the comprehensive passenger transport hub in the region, and k is a positive integer.
Preferably, the site selection index includes:
coordinated matching index w1Demand adaptability index w2And social influence index w3(ii) a Wherein the harmonization matchability index w1Involving a degree of coordination w with the overall plan of the city11Degree of coordination w with various transportation modes12Degree of coordination w with urban road wire network layout13(ii) a The demand adaptability index w2Including pivot service radiation range w21Hub construction scale adaptability w22Future development reserved space w of hub23(ii) a The social influence index w3Including the degree of influence w on the load of the road network around the hub31Degree of influence w on urban population and industrial layout32Influence degree w on urban environment33。
Preferably, the constructing a factor set according to the site selection index and determining an evaluation set includes:
dividing the site selection index to obtain four factor sets W ═ W1，w2，w3}，w1＝{w11,w12,w13},w2＝{w21,w22,w23},w3＝{w31,w32,w33Each factor set contains three indexes; the evaluation set is { excellent, good, general, poor }.
Preferably, a judgment matrix and an evaluation matrix of the factor set are constructed to obtain evaluation results of each site selection index; and performing score assignment on the evaluation grades in the evaluation set, multiplying the evaluation grade scores and the evaluation results of the corresponding grades, and summing to obtain the charm value of the pivot point.
Specifically, the implementation process of the steps is as follows:
step 1: qualitative analysis of influence factors of site selection layout of comprehensive passenger transport hub is keyAnd the influence factors are used as site selection indexes to construct an charm index system. The address index system standard layer comprises a coordination matching index w1Demand adaptability index w2And social influence index w3(ii) a Wherein the harmonization matchability index w1Involving a degree of coordination w with the overall plan of the city11Degree of coordination w with various transportation modes12Degree of coordination w with urban road wire network layout13(ii) a The demand adaptability index w2Including pivot service radiation range w21Hub construction scale adaptability w22Future development reserved space w of hub23(ii) a The social influence index w3Including the degree of influence w on the load of the road network around the hub31Degree of influence w on urban population and industrial layout32Influence degree w on urban environment33。
Step 2: and selecting a factor set. Dividing the factor set according to evaluation criteria: w ═ W1，w2，w3}，w1＝{w11,w12,w13},w2＝{w21,w22,w23},w3＝{w31,w32,w33}
And step 3: and determining an evaluation set. The evaluation set was determined by four grades of excellence, good, generally, poor: { Excellent v1V. good2In general v3Poor v4}
And 4, step 4: and calculating the importance degree coefficient of each factor by using an analytic hierarchy process.
The analytic hierarchy process for calculating the weight distribution coefficient in the step 4 comprises the following steps:
s41, representing the factor W in the factor set W by a 1-9 scale methodiRelative to wjBased on this construction, the determination matrix U is as follows:
s42, normalizing the column vector of each column of the determination matrix U, the calculation formula is as follows:
s43, result M obtained for S42ijIs summed, the calculation formula is as follows:
s44, result M obtained for S43iNormalization processing is carried out to obtain the characteristic vector A of the factor set W ═ a1,a2,a3In which a is1,a2,a3Respectively represent indexes W in the factor set W1,w2,w3The calculation formula of the weight coefficient (c) is as follows:
and S45, performing consistency check on the judgment matrix U.
The consistency check process in S45 is as follows:
s451, calculating the maximum characteristic root lambda of the judgment matrix UmaxThe calculation formula is as follows:
s452, calculating a consistency index CI by using the order f of the judgment matrix, wherein the calculation formula is as follows:
s453, the consistency ratio CR is calculated using the calculation result of S452 and the random consistency index RI corresponding to the order f, and the calculation formula is as follows:
s454, if the calculation result CR of S453 is less than 0.1, the judgment matrix U constructed in S41 is considered to satisfy the consistency check, otherwise, the judgment matrix U is to be reconstructed.
S46, aiming at the factor sets w respectively1,w2,w3Repeating the above steps S41 to S45, calculating the corresponding weight distribution coefficients: a. the1,A2,A3。
And 5: and calculating an evaluation result by using a multi-stage fuzzy evaluation method.
The multi-stage fuzzy evaluation method for calculating the evaluation result in the step 5 comprises the following steps:
s51, evaluating each factor by using an expert scoring method to obtain a factor set w1,w2,w3Evaluation matrix R of1,R2,R3
Further, the specific process of the expert scoring method in step S51 is as follows:
and S511, designing an expert questionnaire based on each index.
S512, issuing a questionnaire, and counting the votes with four grades of excellent, good, common and poor in evaluation by using a professional voting mode
S513, obtaining the matrix element r of the evaluation matrix by using the mode of grade ticket number/expert numberij
S52, adopting respective utilization factor set w1,w2,w3The weight distribution coefficient A1，A2，A3And a corresponding evaluation matrix R1,R2,R3And performing fuzzy comprehensive evaluation of the first layer, wherein the calculation formula is as follows:
s53, performing the second-layer fuzzy comprehensive evaluation by using the calculation result of S52 and the weight distribution coefficient A of the factor set W, wherein the calculation formula is as follows:
step 6: and (4) calculating the charm value by adopting a comprehensive calculation method based on evaluation grade assignment in evaluation concentration.
Further, the charm calculation value in step 6 is obtained by the following comprehensive calculation method:
s61, the evaluation grades collected in the evaluation group are assigned with scores such that excellent is 95, good is 80, generally 65, and poor is 50.
And S62, multiplying the evaluation grade scores and the evaluation results of the corresponding grades obtained in the step S53, and summing the results to obtain the charm value of the node, wherein the calculation formula is as follows:
G＝95×b1+80×b2+65×b3+50×b4 (10)
and 7: repeating the steps 1 to 6 for all nodes in the target area, sequencing the obtained charm values from large to small, and taking K nodes from high to low according to the charm as an alternative point set K of the comprehensive passenger transport hub in the area.
S2: and acquiring optimization parameter data of each pivot point in the alternative pivot point set, and inputting the optimization parameter data into an urban group comprehensive passenger transport pivot point layout optimization model, wherein the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on the transfer times among the pivot points and the transportation mode.
Preferably, the constructing of the urban group integrated passenger transport hub layout optimization model includes:
the passenger station is divided into an integrated passenger transport pivot point and a non-integrated passenger transport pivot point, and the transport modes between the pivot points are divided into a direct transport mode and an indirect transport mode;
and setting a target function, decision variables and constraint conditions of the model, and constructing the urban group comprehensive passenger transport pivot point layout optimization model based on the transfer times among the pivot points and the transportation mode.
Preferably, the objective function comprises:
the method comprises the following steps of minimizing a first objective function by comprehensively considering the total operation cost of the passenger terminal, minimizing a second objective function by comprehensively considering the secondary transfer among terminals and the total transportation cost selected by different transportation modes, and minimizing a third objective function by comprehensively considering the secondary transfer among terminals and the transfer transportation time selected by different transportation modes.
Preferably, the setting of the decision variables comprises:
setting a 0-1 decision variable which represents whether the alternative point in the target area is selected as the integrated passenger transport pivot point or not;
setting a 0-1 decision variable which indicates whether the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport hub or not;
setting a decision variable 0-1 for indicating whether the passenger flow of a certain origin-destination point i-j in the target area is directly transported;
setting a 0-1 decision variable which represents whether a traffic mode h is selected from a starting point i to a comprehensive passenger transport pivot point k when the passenger flow of a certain destination point i-j in a target area is transferred through the comprehensive passenger transport pivot point;
setting a 0-1 decision variable which indicates whether a traffic mode h is selected from a comprehensive passenger transport pivot point k to a comprehensive passenger transport pivot point m when the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point;
and setting a 0-1 decision variable which represents whether the traffic mode h is selected from the comprehensive passenger transport pivot point m to the destination j when the passenger flow of a certain destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point.
Preferably, the constraints of the model include:
the method comprises the following steps of comprehensive passenger transport hub station quantity limitation, transport mode selection limitation, comprehensive passenger transport hub entrance and exit passenger flow conservation limitation, transit passenger flow composition limitation, direct transport passenger flow composition limitation, origin-destination total passenger flow composition limitation, node passenger flow generation amount and passenger flow attraction amount balance limitation, comprehensive passenger transport hub capacity limitation, comprehensive passenger transport hub service range and transport mode selection limitation.
Specifically, the implementation process of the steps is as follows:
step 1: reasonable model assumptions are provided for the establishment of an optimization model, and the method is characterized in that the related premise assumptions are as follows:
(1) the method comprises the following steps that N passenger station nodes in a target area are divided into two types of nodes, namely a comprehensive passenger transport hub and a non-comprehensive passenger transport hub, and the comprehensive passenger transport hub nodes are a passenger flow generation place and an attraction place and are a passenger flow gathering and distributing place; the non-comprehensive passenger transport hub node is only considered as a passenger flow generation place and a passenger flow attraction place.
(2) The transport network of the target area may be simplified to a directed graph G ═ (N, L), where N represents two sets of nodes in the transport network, N ═ 1,2, … N }; l represents the line set between the passenger station nodes, L ═ Lij}, mark lij(i, j) represents a directed arc pointing from node i to node j, and the length of the directed arc represents the travel distance dijThe transportation line between the nodes at least comprises one of three transportation modes of road transportation, railway transportation and air transportation.
(3) The transportation mode among all nodes in the target area is divided into a direct transportation mode and an indirect transportation mode, the indirect transportation mode refers to the situation that the passenger flow among the origin-destination points is transported through a comprehensive passenger transport hub point for transfer, and a secondary transfer scene is considered.
Step 2: on the basis of the determination of the alternative point set K, collecting and acquiring various parameter data required by the optimization model, and preparing basic data for model input, wherein the parameter data comprises:
(1) and acquiring the node number N of all passenger transport stations in the target area and the number K of all alternative hub stations, and determining the final comprehensive passenger transport hub number M to be planned.
(2) And the construction of the comprehensive passenger transport pivot point k is fixed.
(3) The unit transfer cost is distributed through the integrated passenger transport pivot point k.
(4) Grasping the connection of transportation modes and the current situation of network layout among all the alternative hub stations
(5) Obtaining passenger flow OD matrix data F between each pair of origin-destination points among all nodes in a target areaij
(6) And passenger flow OD matrix data of each pair of origin-destination points among all nodes in the target area in different transportation modes (including three transportation modes of highways, railways and aviation) are obtained.
(7) And acquiring distance data among all nodes in the target area.
(8) And acquiring unit transportation cost of transportation in each transportation mode among all nodes in the target area.
(9) And acquiring the planned passenger flow when the alternative node k in the target area is selected as the comprehensive passenger transport hub.
(10) Respectively acquiring unit shortest travel time of each transportation mode (comprising three transportation modes of highway, railway and aviation) between (N-K) non-comprehensive passenger transport hub nodes and K comprehensive passenger transport hub alternative nodes
(11) And respectively acquiring the maximum acceptable travel time of travelers of each transportation mode (comprising three transportation modes of highway, railway and aviation) between the (N-K) non-comprehensive passenger transport hub nodes and the K comprehensive passenger transport hub alternative nodes.
(12) Further, acquiring the passenger flow occurrence O of all nodes by using the data (5) in the step 1iAnd the volume of attraction of passenger flow DjData, the calculation formula is as follows:
Oi＝∑j∈N Fij (11)
Dj＝∑i∈N Fij (12)
and step 3: and constructing an urban group comprehensive passenger transport hub layout optimization model considering the secondary transfer among hubs and the connection of different transportation modes.
Further, the construction of the urban group integrated passenger transport hub layout optimization model in the step 3 comprises the following processes:
s31, setting decision variables, wherein the required decision variables are as follows:
(1) setting a 0-1 decision variable which represents whether the alternative node k in the target area is selected as the integrated passenger transport pivot point or not;
(2) setting a 0-1 decision variable which indicates whether the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport hub or not;
(3) setting a decision variable 0-1 for indicating whether the passenger flow of a certain origin-destination point i-j in the target area is directly transported;
(4) setting a 0-1 decision variable which represents whether a traffic mode h is selected from a starting point i to a comprehensive passenger transport pivot point k when the passenger flow of a certain destination point i-j in a target area is transferred through the comprehensive passenger transport pivot point;
(5) setting a 0-1 decision variable which indicates whether a traffic mode h is selected from a comprehensive passenger transport pivot point k to a comprehensive passenger transport pivot point m when the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point;
(6) setting a 0-1 decision variable which indicates whether a traffic mode h is selected from a comprehensive passenger transport pivot point m to a destination j when the passenger flow of a certain destination point i-j in a target area is transferred through the comprehensive passenger transport pivot point;
and S32, setting an objective function of the comprehensive passenger transport hub layout optimization model. The method comprises the steps of considering minimization of the total operation cost of the comprehensive passenger transport hub in a target area, comprehensively considering minimization of the total transport cost under selection of the secondary transfer and different transportation modes, and comprehensively considering minimization of the total travel time of the transfer transportation under selection of the secondary transfer and different transportation modes. The corresponding objective functions are respectively as follows:
min z1＝∑k∈Kyk(Fk+Ckqk) (13)
min z2＝∑i∈N∑j∈N∑k∈K∑m∈M∑h∈H∑l∈H∑s∈H(CihkdikQihkZihk+CklmdkmQklmZklm+CmsjdmjQmsjZmsj)·Xikmj+∑i∈N∑j∈N∑h∈HCihjdijqihjZihjXij (14)
min z3＝∑i∈N∑j∈N∑k∈K∑m∈M∑h∈H∑l∈H∑s∈H(tihkQihkZihk+tklmQklmZklm+tmsjQmsjZmsj)Xikmj (15)
and S33, setting the constraint conditions of the comprehensive passenger transport hub layout optimization model.
Further, the constraint condition setting process described in S33 is as follows:
s331, setting the comprehensive passenger transport hub station number limit constraint to be constructed in the target area:
∑k∈K yk＝M (16)
s332, setting transportation mode selection constraints in the target area, namely only one of a direct transportation mode of direct transportation and a transit mode of indirect transportation through a comprehensive passenger transport hub can be selected:
s333, setting a constraint which represents that the transportation service of the transshipment between the hubs can be carried out only when the alternative node k is established as the integrated pivot point in the target area:
s334, setting a passenger flow volume conservation constraint for indicating the entrance and exit of the comprehensive passenger transport hub k in the target area, namely the passenger flow volume transferred through the comprehensive passenger transport hub k in the passenger flow volume of the origin-destination point i-j is composed of secondary transfer of various transport modes of i-k-m-j and primary transfer passenger flow volume of various transport modes of i-k-j:
s335, setting a passenger flow inlet and outlet conservation constraint representing the comprehensive passenger transport hub m in the target area, namely the passenger flow inlet and outlet conservation constraint of the comprehensive passenger transport hub m when secondary transfer of each transport mode is carried out in the passenger flow of the origin-destination point i-j through i-k-m-j:
s336, setting a transit passenger flow composition constraint in the passenger flow of the origin-destination point i-j in the target area, namely the transit passenger flow composition constraint comprises the primary transit passenger flow of each transportation mode and the secondary transit passenger flow of each transportation mode:
s337, setting and representing origin-destination direct passenger transportation volume in the target area to form constraint, namely the direct passenger transportation volume is formed by three transportation modes:
s338, setting passenger flow composition constraint representing origin-destination points i-j in the target area, namely comprising transit passenger flow and direct passenger flow:
s339, setting balance constraint of the generation amount and the attraction amount of the nodes in the target area:
s3310, setting the capacity limit constraint representing the comprehensive passenger transport hub in the target area, namely the passenger flow q transferred through the comprehensive passenger transport hub kkPlanned passenger flow Q which cannot exceed the hubkk(ii) a Passenger flow q transferred through comprehensive passenger transport hub mmPlanned passenger flow Q which cannot exceed the hubmm：
S3311, setting comprehensive passenger transport hub service range and transportation mode selection constraint in the target area, namely when the time from a starting point i to a comprehensive passenger transport hub point k in a certain transportation mode is selected to be greater than the maximum acceptable time, not selecting the transportation mode, and if each transportation mode is greater than the maximum acceptable time, not serving the passenger flow of the starting point i by the hub k; similarly, when a transportation mode is selected, the time from the integrated passenger transport pivot point k to the integrated passenger transport pivot point m is greater than the maximum acceptable time, the transportation mode is not selected, and if each transportation mode is greater than the maximum acceptable time, the junction m does not perform secondary transit service on the passenger flow of the integrated passenger transport pivot point k:
ykTihk≥Zihktihk (31)
ymTklm≥Zklmtklm (32)
s3312, setting a restriction which indicates that the transportation mode of transportation is selected only when the passenger flow of the origin-destination point i-j passes through the transit of the comprehensive passenger transport hub point in the target area:
s3313, the decision variable constraint described in S31 representing the target region is set, and the following equations correspond to the descriptions in (1), (2), (3), (4), (5), (6) in S31, respectively:
wherein the meaning of each symbol in the above formula is shown in the following table:
s3: and solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
Specifically, based on the constructed urban group integrated passenger transport hub layout optimization model considering the secondary transfer among hubs and the connection of different transportation modes, the model input parameters required to be obtained in the step S1 are input, the model can be solved by using a heuristic algorithm, the model belongs to a nonlinear mathematical programming problem, and the genetic algorithm has effectiveness in solving the problem and can be theoretically applied to solving the mathematical optimization model. And solving can be realized by utilizing a heuristic algorithm in Matlab software, and a cooperative optimization layout scheme of the urban complex comprehensive passenger transport hub is output.
The charm-based screening method for the urban group comprehensive passenger transport hub alternative points is adopted for selecting the comprehensive passenger transport hub alternative point set, belongs to a qualitative and quantitative combination mode, firstly, the qualitative influence factors influencing the site selection are considered comprehensively, a charm index system is constructed, then, the qualitative indexes are subjected to comprehensive quantitative processing by utilizing a comprehensive calculation method of grading assignment based on hierarchical analysis and a multi-level fuzzy evaluation method, and finally, the possibility and the attraction of the nodes serving as the comprehensive passenger transport hub stations are measured by adopting quantitative charm values. The method gives consideration to qualitative factors such as social economy, surrounding environment and the like, realizes the conversion from qualitative analysis to qualitative calculation, can provide an effective thought for the preliminary screening of the nodes in the large-scale area of the urban mass, realizes the reasonable reduction of the alternative range, and is favorable for improving the efficiency of the subsequent layout optimization based on the mathematical model.
The embodiment aims at the construction of the comprehensive passenger transport hub collaborative layout optimization model, and comprehensively considers the situation that transfer transportation and different transportation modes are linked between the comprehensive passenger transport hubs, so that the model is more practical. An objective function of minimizing total transportation cost and minimizing total transit time is designed by comprehensive consideration of overall secondary transit and selection of three transportation modes, conditions such as transportation mode selection constraint, junction service range limitation combined with the transportation modes and the like are set in constraint conditions, so that the model not only can solve the problem of selecting station layout of M comprehensive passenger transportation junction nodes which are finally required to be determined from K alternative junction stations in N nodes, but also can output the selection of a transportation mode and a transportation route for each node, namely the passenger flow generated from a starting non-comprehensive passenger transportation junction node i is to select a direct transportation route i-j to reach an end non-passenger transportation junction station j or select an indirect route i-K-M-j which is subjected to secondary transit through a comprehensive passenger transportation junction point K and a comprehensive passenger transportation junction node M to reach the end non-comprehensive passenger transportation junction station j, or an indirect route i-k-j which is subjected to one-time transfer through the comprehensive passenger transport pivot point k is selected to arrive at the destination passenger station j, so that the problem of obtaining the transport route list between destination points can be solved; the set of passenger flow generating nodes served by the integrated passenger terminal k can be output. In addition, the model can output the transportation mode selection conditions of the direct route i-j and the indirect route i-k-m-j or i-k-j. The output result based on the model can provide certain decision basis for the position selection of the comprehensive passenger transport pivot point in the urban group and the arrangement situation of the transportation mode in the pivot.
Example 2
Fig. 2 is a schematic diagram of a cooperative layout optimization system of an urban complex integrated passenger transport hub. As shown in fig. 2, the present invention further provides a cooperative layout optimization system for an urban complex integrated passenger transportation hub, the system comprising:
the screening module is used for selecting a target urban group area and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model;
the input module is used for acquiring optimization parameter data of each pivot point in the alternative pivot point set and inputting an urban group comprehensive passenger transport pivot point layout optimization model, and the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on transit times among the pivot points and a transportation mode;
and the optimization module is used for solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
The specific implementation process of the method steps executed by each module in this embodiment 2 is the same as the implementation process of each step in embodiment 1, and is not described herein again.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A cooperative layout optimization method for an urban group integrated passenger transport hub is characterized by comprising the following steps:
s1: selecting a target urban group area, and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model;
s2: acquiring optimization parameter data of each pivot point in the alternative pivot point set, and inputting an urban group comprehensive passenger transport pivot point layout optimization model, wherein the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on the transfer times among the pivot points and the transportation mode;
s3: and solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
2. The method of claim 1, wherein the constructing of the urban mass transit integrated pivot point screening model comprises:
analyzing influence factors of site selection layout of the comprehensive passenger transport hub, and determining site selection indexes;
constructing a factor set according to the site selection indexes, and determining an evaluation set;
calculating the weight distribution coefficient of each factor set and the evaluation result of each pivot point;
assigning a calculation charm value to the evaluation grade in the evaluation set, wherein the charm value is used for screening pivot points to obtain alternative pivot points;
and (4) charm sequencing is carried out on the charm values from large to small, k front nodes are taken from high to low according to the charm and serve as an alternative point set of the comprehensive passenger transport hub in the region, and k is a positive integer.
3. The method of claim 2, wherein the site selection indicator comprises:
coordinated matching index w1Demand adaptability index w2And social influence index w3(ii) a Wherein the harmonization matchability index w1Involving a degree of coordination w with the overall plan of the city11Degree of coordination w with various transportation modes12Degree of coordination w with urban road wire network layout13(ii) a The demand adaptability index w2Including pivot service radiation range w21Hub construction scale adaptability w22Future development reserved space w of hub23(ii) a The social influence index w3Including the degree of influence w on the load of the road network around the hub31Degree of influence w on urban population and industrial layout32To cityDegree of influence w of the environment33。
4. The method of claim 3, wherein constructing a set of factors from the site selection metrics and determining a set of evaluations comprises:
dividing the site selection index to obtain four factor sets W ═ W1，w2，w3}，w1＝{w11,w12,w13},w2＝{w21,w22,w23},w3＝{w31,w32,w33Each factor set contains three indexes; the evaluation set is { excellent, good, general, poor }.
5. The method according to claim 4, wherein a judgment matrix and an evaluation matrix of the factor set are constructed to obtain evaluation results of each site selection index; and performing score assignment on the evaluation grades in the evaluation set, multiplying the evaluation grade scores and the evaluation results of the corresponding grades, and summing to obtain the charm value of the pivot point.
6. The method of claim 1, wherein constructing the urban mass transit hub layout optimization model comprises:
the passenger station is divided into an integrated passenger transport pivot point and a non-integrated passenger transport pivot point, and the transport modes between the pivot points are divided into a direct transport mode and an indirect transport mode;
and setting a target function, decision variables and constraint conditions of the model, and constructing the urban group comprehensive passenger transport pivot point layout optimization model based on the transfer times among the pivot points and the transportation mode.
7. The method of claim 6, wherein the objective function comprises:
the method comprises the following steps of minimizing a first objective function by comprehensively considering the total operation cost of the passenger terminal, minimizing a second objective function by comprehensively considering the secondary transfer among terminals and the total transportation cost selected by different transportation modes, and minimizing a third objective function by comprehensively considering the secondary transfer among terminals and the transfer transportation time selected by different transportation modes.
8. The method of claim 6, wherein setting a decision variable comprises:
setting a 0-1 decision variable which represents whether the alternative point in the target area is selected as the integrated passenger transport pivot point or not;
setting a 0-1 decision variable which indicates whether the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport hub or not;
setting a decision variable 0-1 for indicating whether the passenger flow of a certain origin-destination point i-j in the target area is directly transported;
setting a 0-1 decision variable which represents whether a traffic mode h is selected from a starting point i to a comprehensive passenger transport pivot point k when the passenger flow of a certain destination point i-j in a target area is transferred through the comprehensive passenger transport pivot point;
setting a 0-1 decision variable which indicates whether a traffic mode h is selected from a comprehensive passenger transport pivot point k to a comprehensive passenger transport pivot point m when the passenger flow of a certain origin-destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point;
and setting a 0-1 decision variable which represents whether the traffic mode h is selected from the comprehensive passenger transport pivot point m to the destination j when the passenger flow of a certain destination point i-j in the target area is transferred through the comprehensive passenger transport pivot point.
9. The method according to claim 6 or 7, wherein the constraints of the model comprise:
the method comprises the following steps of comprehensive passenger transport hub station quantity limitation, transport mode selection limitation, comprehensive passenger transport hub entrance and exit passenger flow conservation limitation, transit passenger flow composition limitation, direct transport passenger flow composition limitation, origin-destination total passenger flow composition limitation, node passenger flow generation amount and passenger flow attraction amount balance limitation, comprehensive passenger transport hub capacity limitation, comprehensive passenger transport hub service range and transport mode selection limitation.
10. An urban group integrated passenger transport hub collaborative layout optimization system, the system comprising:
the screening module is used for selecting a target urban group area and determining an alternative pivot point set in the target urban group area according to an urban group comprehensive passenger transport pivot point screening model;
the input module is used for acquiring optimization parameter data of each pivot point in the alternative pivot point set and inputting an urban group comprehensive passenger transport pivot point layout optimization model, and the urban group comprehensive passenger transport pivot point layout optimization model is constructed based on transit times among the pivot points and a transportation mode;
and the optimization module is used for solving the urban group comprehensive passenger transport hub connection point layout optimization model and outputting an urban group comprehensive passenger transport hub collaborative optimization layout scheme.
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