Railway beam yard site selection method based on V-K combinatorial algorithm

Abstract

The invention discloses a railway beam yard site selection method based on a V-K combinatorial algorithm. The method comprises the following steps: S1, obtaining a bridge center coordinate in a region to be subjected to site selection and determining a constraint condition; s2, searching a global optimal solution; s3, acquiring a local optimal solution; s4, constructing a global optimal solution; s5, obtaining a final beam field position set; according to the method, multiple groups of different initial solutions can be obtained randomly according to the strategy, so that the final result is the global optimal solution as far as possible, the situation that the local optimal solution is not ideal possibly under the condition that only one group of initial solutions exist is avoided, the beam field address close to the local optimal solution can be rapidly obtained through the V-K combinatorial algorithm, and the method has the advantages of being high in practicability and the like. A lot of time consumed by using a mountain climbing algorithm in the whole process can be reduced. Compared with a conventional single bridge site selection algorithm, the V-K algorithm is not liable to fall into local optimum, and the consumed time is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the field of transportation engineering, and in particular to a railway beam yard site selection method based on a VK combination algorithm. Background Art

[0002] The beam yard is a place used for the production and temporary storage of precast concrete simply supported beams in bridge engineering. The precast simply supported beams of bridges are prefabricated in the factory and then transported to the construction site for hoisting and erection.

[0003] The factors that need to be considered in beam yard site selection are very complex. It is necessary to fully investigate the needs and difficulties in advance, establish a relevant mathematical model, and use an efficient algorithm to find the optimal location.

[0004] At present, there are the following problems to be solved in the optimization of beam site selection:

[0005] (1) The optimization model for beam yard site selection needs to consider many factors, including transportation distance, capacity limitation, bridge distribution, topography, road conditions, policy planning restrictions, etc. It is very difficult to establish an accurate mathematical model that includes all factors. The acquisition of relevant parameters and the continuous correction and calibration of the model require a lot of work to complete.

[0006] (2) The optimization of beam yard site selection requires processing a large amount of bridge location data and calculating the transportation distance from each candidate point to each bridge. The complex constraints make the calculation very large. Compared with simple problems, it is easy to fall into the local optimal solution and it is difficult to reach the global optimal solution. It is necessary to adopt advanced intelligent optimization algorithms such as genetic algorithms and simulated annealing, and to make corrections with artificial experience to increase the probability of converging to the global optimal solution.

[0007] (3) The site selection of the beam yard can have different optimization objectives such as minimum transportation distance, minimum transportation time, and minimum comprehensive cost. The selection of these objective functions will have a great impact on the final optimization plan. When the actual conditions change, the model needs to be updated and re-solved in time, otherwise the existing plan may lose its practical significance and cannot cope with new situations.

[0008] (4) After the optimal beam site location is determined, the actual implementation will encounter many uncertainties such as site acquisition, construction permit, material supply, and machinery deployment. It is also necessary to coordinate the supply chain with the prefabricated beam factory and transportation company, and consider safety risks during construction. These uncertainties will cause certain difficulties in the implementation of the final plan.

[0009] (5) From design to implementation, the entire process needs to be fully supervised, and transportation time, cost, quality, etc. need to be monitored and compared with model predictions to detect deviations and make adjustments as early as possible. The final results also need to be evaluated from multiple angles to ensure that they meet project requirements.

[0010] In summary, the optimization of beam site selection is a highly comprehensive decision-making problem. It is necessary to fully consider various factors, adopt scientific algorithms and combine them with practice to achieve the best results. Summary of the invention

[0011] In order to solve the problems in the background technology, the present invention provides a railway beam yard site selection method based on the VK combination algorithm, which has comprehensive considerations, high search efficiency, accurate results, short time consumption and strong usability.

[0012] To this end, the technical solution of the present invention is as follows:

[0013] A railway beam yard site selection method based on a VK combination algorithm comprises the following steps:

[0014] S1, obtaining the center coordinates of the bridge in the area to be selected and determining the constraint conditions: the constraint conditions are used to determine whether the bridge center coordinate set composed of the bridge center coordinates and the beam yard position in the area to be selected meet the specifications for bridge construction;

[0015] S2, finding the global optimal solution, includes the following steps:

[0016] S21, generate the initial solution S′:

[0017] The bridge center coordinates are randomly divided using a strategy to obtain several bridge center coordinate sets, and then the bridge center coordinate sets are verified using the constraints obtained by S1 until an initial solution S′={S1′,S2′,S3′,…S′} is generated that satisfies the constraints. n ,…,S′ N}, n is the number of the beam yard, S′ n is the bridge center coordinate set corresponding to the nth beam field, 1≤n≤N; then arrange the elements in each bridge center coordinate set in the initial solution S′ according to their corresponding mileage order;

[0018] S22, use the VK combination algorithm to generate a local optimal solution:

[0019] The VK combination algorithm is as follows: traverse each element in the initial solution S′, if S′ n If the number of inner bridge center coordinates is an odd number, the coordinates of the middle element are selected as the beam site position r n , if S′ n If the number of inner bridge center coordinates is an even number, the average value of the coordinates of the two middle elements is selected as the beam site position r n ; Obtain a beam field position set consisting of several beam field positions;

[0020] S23, using the constraint conditions of S1 to judge the beam site position set obtained in S22, if the constraint conditions are met, then go to S3, if not, then return to step S21 to regenerate the initial solution;

[0021] S3, obtaining the local optimal solution, includes the following steps:

[0022] S31, input the beam field location set obtained in S23 into the hill climbing algorithm to generate each beam field location r n The local optimal solution R n , and combine them into a set of local optimal solutions;

[0023] S32, using the constraint conditions in step S1 to judge the set of local optimal solutions obtained in step S31, if the constraint conditions are met, proceed to S4, if not, return to S31 until the constraint conditions are met;

[0024] S4, constructing the global optimal solution, includes the following steps:

[0025] S41, establish evaluation function:

[0026] The evaluation function is specifically the sum of the total transportation distances from all bridge center points within each beam yard to their corresponding beam yards;

[0027] S42, calculate the global optimal solution:

[0028] The one with the smallest function value of the evaluation function among multiple local optimal solutions of the same beam field is selected as the global optimal solution of the corresponding beam field position, and finally the global optimal solutions of all beam fields are combined as a set of global optimal solutions;

[0029] S5, get the final beam site location set:

[0030] Steps S2 to S4 are used cyclically to generate a set of multiple sets of global optimal solutions, and then they are evaluated using the global evaluation function f′. The set of global optimal solutions with the smallest function value in the global evaluation function f′ is taken as the final beam site position set P and output. The global evaluation function f′ is shown in the following formula:

[0031]

[0032] Among them, p′ k is the local optimal solution R n The coordinates of the center of the covered bridge, k is the bridge number, k∈[1,K], K is the total number of bridges.

[0033] Step S1 specifically includes the following steps:

[0034] S11, construct the set S of bridge center coordinate sets:

[0035] Get the coordinates of the bridge center in the area to be selected and record it as p k Then, it is assumed that at most N beam yard addresses need to be selected in the area to be selected, and the location of the beam yard is r n , n = 1, 2, 3, ..., N, set the coordinate set of the bridge center of the bridge covered by the beam field as S n , the set of bridge center coordinate sets obtained by combining all the divided bridge center coordinate sets is called S = {S1, S2, S3, ... S n ,…,S N};

[0036] S12, construct constraints.

[0037] The constraints are specifically:

[0038]

[0039] Among them, max(S n )-min(S n ) represents the bridge center coordinate set S n The maximum distance between the centers of two different bridges;

[0040] In formula (2), |S n | represents the bridge center coordinate set S n The number of bridges included in;

[0041] In formula (3), high(r n ) represents beam field r n The height of the pier;

[0042] Formula (4) indicates that it is impossible to set up a beam yard within the tunnel construction site and continuous beam construction site;

[0043] Formula (5) indicates that beam yards cannot be set up in basic farmland and environmental protection zones.

[0044] Preferably, A≤40; B≤700; C≤20; A, B and C are all set according to actual conditions.

[0045] The evaluation function of step S41 is as follows:

[0046]

[0047] Among them, f is the evaluation function, p′ k is the local optimal solution of the beam field R n The coordinates of the center points of bridges within the coverage area.

[0048] There are multiple initial solutions obtained in S21, and any result randomly generated by the strategy that satisfies the constraint condition is used as the initial solution.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. The strategy in the present invention can randomly obtain multiple groups of different initial solutions, so that the final result is as global as possible. It avoids the situation where there is only one group of initial solutions and the local optimal solution is not ideal. In addition, the VK combination algorithm of the present invention can quickly obtain the beam yard address close to the local optimal solution, which can reduce the large amount of time consumed by using the hill climbing algorithm throughout the process. Compared with the previous single bridge site selection algorithm, the VK algorithm is not easy to fall into the local optimum, and the time consumption is greatly reduced.

[0051] 2. The present invention enhances the ability to handle constraints. In view of various constraints of the beam site selection problem, such as the transportation distance range, the number of beam holes, etc., the algorithm constructs a strict feasible solution filtering mechanism, which makes the randomly generated solution feasible and verifies the feasibility of the solution in the iterative process, effectively controlling the output of the results. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0054] In bridge construction, the production, transportation and erection of precast concrete simply supported beams are key links. Due to the large number of bridge piers and the long distance between them, the site selection of the beam yard is crucial to ensure efficient and reasonable production and transportation. The site selection of the beam yard is the process of selecting a suitable site to set up the beam yard based on the project situation and under the premise of meeting certain conditions. The site selection of the beam yard needs to consider many factors.

[0055] First, the location of the beam yard is related to the transportation distance. If the beam yard is too far from the bridge, it will increase the transportation time and cost. Secondly, the area of ​​the beam yard must meet production needs and can usually accommodate 300-1000 beams. In addition, transportation is also limited by transportation capacity, and only a certain number of beams can be transported at a time. Therefore, the location of the beam yard not only affects the transportation of a single bridge, but also affects the comprehensive supply of multiple surrounding bridges.

[0056] In terms of restrictions, the site selection of the beam yard needs to avoid ecological protection areas, basic farmland and other areas. Traffic conditions are also very important, and it must be convenient for transport vehicles to enter and exit. In addition, the height difference of the river beach area under the bridge is large, and terrain restrictions need to be considered. The distance between the piers in the continuous beam area is small, and it is impossible to set up a beam yard. If the location of the beam yard is reasonably selected, the transportation distance can be greatly reduced and production efficiency can be improved. Otherwise, it will increase time and transportation costs and affect the construction progress. Therefore, an optimization model needs to be adopted to comprehensively consider various factors in order to solve the optimal beam yard location. In terms of production, the prefabricated beam plant needs to be located in an open area to facilitate the production and storage of beam molds. At the same time, its infrastructure such as electricity and water resources needs to be in place.

[0057] The railway beam yard site selection method based on the VK combination algorithm of the present invention comprises the following steps:

[0058] S1, constructing constraints, specifically including the following steps:

[0059] S11, construct the set S of bridge center coordinate sets:

[0060] Get the coordinates of the bridge center in the area to be selected and record it as p k , k is the bridge number, k∈[1,K], K is the total number of bridges; then it is assumed that at most N beam yard addresses need to be selected in the site selection area, and the location of the beam yard is r n , n = 1, 2, 3, ..., N, set the coordinate set of the bridge center of the bridge covered by the beam field as S n , the set of bridge center coordinate sets obtained by combining all the divided bridge center coordinate sets is called S = {S1, S2, S3, ... S n ,…,S N}.

[0061] S12, build constraints:

[0062] In order to obtain a feasible solution, constraints are imposed on the coordinate set of the bridge center and the position of the beam field, as shown in the following formula:

[0063]

[0064] Wherein, formula (1) indicates that the maximum diameter of a single beam field is 40 km, max(S n )-min(S n ) represents the bridge center coordinate set S n The maximum distance between two different bridge centers, the coverage diameter can also be adjusted according to actual conditions;

[0065] Formula (2) indicates that a single beam yard can accommodate up to 700 bridges, |S n | represents the bridge center coordinate set S nThe number of bridges included in the project and the number of bridges that a single beam yard can accommodate can also be adjusted according to actual conditions;

[0066] Formula (3) indicates that the maximum pier height at the beam field site is 20 meters, high(r n ) represents beam field r n The height of the pier;

[0067] Formula (4) indicates that it is impossible to set up a beam yard within the tunnel construction site and continuous beam construction site;

[0068] Formula (5) indicates that beam yards cannot be set up in basic farmland and environmental protection zones.

[0069] S2, finding the global optimal solution of the set S of bridge center coordinate sets, including the following steps:

[0070] S21, generate the initial solution S′:

[0071] The distribution of the beam field in the set of bridge center coordinate sets is randomly divided using strategies, but the randomly generated solution may not meet the constraints of the bridge site selection problem, so it is necessary to verify the part of the bridge center coordinate set in the constraints in S1.2. Until the initial solution S′={S1′,S2′,S3′,…S′ that meets the constraints is generated n ,…,S′ N}, and arrange the elements in the coordinate set of each bridge center in the initial solution S′ according to their corresponding mileage order. There can be multiple initial solutions, and any result randomly generated by the strategy that meets the constraints can be used as the initial solution.

[0072] S22, use the VK combination algorithm to generate a local optimal solution:

[0073] The VK combination algorithm is as follows: traverse each element in the initial solution S'. If S' n If the number of inner bridge center coordinates is an odd number, the coordinates of the middle element are selected as the beam site position r n , if S′ n If the number of inner bridge center coordinates is an even number, the average value of the coordinates of the two middle elements is selected as the beam site position r n ; Get the beam site position r n The beam yard location set.

[0074] S23, verify the feasibility, use the constraint conditions of S12 to judge the beam site position set obtained in S22, if the constraint conditions are met, enter S3, if not, return to S21 to regenerate the initial solution.

[0075] S3, obtain the local optimal solution:

[0076] S31, input the beam field location set obtained in S23 into the hill climbing algorithm to generate each beam field location r n The local optimal solution R n , and combined into a set of local optimal solutions; the hill climbing algorithm regards the solution set as a mountain-shaped landscape of the height or value of the objective function, always moving upwards, and finally obtaining a local peak solution. The purpose of introducing hill climbing here is to search for the local optimum within the feasible domain, that is, to maximize the optimal division of the classification scheme and minimize the total transportation distance.

[0077] S32, use the constraints of S12 to judge the set of local optimal solutions obtained in S31. If the constraints are met, the local optimal solution R of the beam field is obtained. n If the constraints are not met, go back to S31 until they are met.

[0078] S4, construct the global optimal solution:

[0079] S41, establish evaluation function f:

[0080] The evaluation value of the solution is calculated based on the preset optimization goal, that is, the sum of the total transportation distances from the center points of all bridges within each beam yard to their corresponding beam yards is used, as shown in the following formula:

[0081]

[0082] Among them, p′ k is the local optimal solution of the beam field R n The coordinates of the center points of bridges within the coverage area.

[0083] S42, calculate the global optimal solution:

[0084] Since multiple local optimal solutions of the same beam field may be generated, the function value of the evaluation function f obtained in S41 is used to compare them, and the smallest function value of the evaluation function f is taken as the global optimal solution of the corresponding beam field position. Finally, the global optimal solutions of all beam fields are combined as a set of global optimal solutions.

[0085] S5, get the final beam site location set:

[0086] Steps S2 to S4 are used cyclically to generate multiple sets of global optimal solutions, and then they are evaluated using the global evaluation function f′. The set of global optimal solutions with the smallest function value in the global evaluation function f′ is taken as the final beam site position set P and output. The global evaluation function f′ is shown in the following formula:

[0087]

[0088] Following the above steps, the best beam site location combination can be obtained based on the existing bridge center location. The whole process is iterative and interactive, and multiple combinations of global optimal solutions will be generated during the process. Multiple iterations and adjustments are required to achieve the final result and goal.

Claims

1. A railway beam yard site selection method based on VK combination algorithm, characterized in that: The following steps are involved: S1, obtaining the center coordinates of the bridge in the area to be selected and determining the constraint conditions: the constraint conditions are used to determine whether the bridge center coordinate set composed of the bridge center coordinates and the beam yard position in the area to be selected meet the specifications for bridge construction; S2, finding the global optimal solution, includes the following steps: S21, generate the initial solution S′: The bridge center coordinates are randomly divided using a strategy to obtain several bridge center coordinate sets, and then the bridge center coordinate sets are verified using the constraints obtained by S1 until an initial solution S′={S1′,S2′,S3′,…S′} is generated that satisfies the constraints. n ,…,S′ N }, n is the number of the beam yard, S′ n is the bridge center coordinate set corresponding to the nth beam field, 1≤n≤N; then arrange the elements in each bridge center coordinate set in the initial solution S′ according to their corresponding mileage order; S22, use the VK combination algorithm to generate a local optimal solution: The VK combination algorithm is as follows: traverse each element in the initial solution S′, if S′ n If the number of inner bridge center coordinates is an odd number, the coordinates of the middle element are selected as the beam site position r n , if S′ n If the number of inner bridge center coordinates is an even number, the average value of the coordinates of the two middle elements is selected as the beam site position r n ; Obtain a beam field position set consisting of several beam field positions; S23, using the constraint conditions of S1 to judge the beam site position set obtained in S22, if the constraint conditions are met, then go to S3, if not, then return to step S21 to regenerate the initial solution; S3, obtaining the local optimal solution, includes the following steps: S31, input the beam field location set obtained in S23 into the hill climbing algorithm to generate each beam field location r n The local optimal solution R n , and combine them into a set of local optimal solutions; S32, using the constraint conditions in step S1 to judge the set of local optimal solutions obtained in step S31, if the constraint conditions are met, proceed to S4, if not, return to S31 until the constraint conditions are met; S4, constructing the global optimal solution, includes the following steps: S41, establish evaluation function: The evaluation function is specifically the sum of the total transportation distances from all bridge center points within each beam yard to their corresponding beam yards; S42, calculate the global optimal solution: The one with the smallest function value of the evaluation function among multiple local optimal solutions of the same beam field is selected as the global optimal solution of the corresponding beam field position, and finally the global optimal solutions of all beam fields are combined as a set of global optimal solutions; S5, get the final beam site location set: Steps S2 to S4 are used cyclically to generate a plurality of sets of global optimal solutions, which are then evaluated using the global evaluation function f′, and the set of global optimal solutions with the smallest function value in the global evaluation function f′ is taken as the final beam site position set P and output.

2. The railway beam yard site selection method based on the VK combination algorithm according to claim 1 is characterized in that: Step S1 specifically includes the following steps: S11, construct the set S of bridge center coordinate sets: Get the coordinates of the bridge center in the area to be selected and record it as p k Then, it is assumed that at most N beam yard addresses need to be selected in the area to be selected, and the location of the beam yard is r n , n = 1, 2, 3, ..., N, set the coordinate set of the bridge center of the bridge covered by the beam field as S n , the set of bridge center coordinate sets obtained by combining all the divided bridge center coordinate sets is called S = {S1, S2, S3, ... S n ,…,S N }; S12, construct constraints.

3. The railway beam yard site selection method based on the VK combination algorithm according to claim 2 is characterized in that: The constraints are specifically: Among them, max(S n )-min(S n ) represents the bridge center coordinate set S n The maximum distance between the centers of two different bridges; In formula (2), |S n | represents the bridge center coordinate set S n The number of bridges included in; In formula (3), high(r n ) represents beam field r n The height of the pier; Formula (4) indicates that it is impossible to set up a beam yard within the tunnel construction site and continuous beam construction site; Formula (5) indicates that beam yards cannot be set up in basic farmland and environmental protection zones.

4. The railway beam yard site selection method based on the VK combination algorithm according to claim 3 is characterized in that: A≤40; B≤700; C≤20; A, B and C are set according to actual conditions.

5. The railway beam yard site selection method based on the VK combination algorithm according to claim 1 is characterized in that: The evaluation function of step S41 is as follows: Among them, f is the evaluation function, p′ k is the local optimal solution of the beam field R n The coordinates of the center points of bridges within the coverage area.

6. The railway beam yard site selection method based on the VK combination algorithm according to claim 1 is characterized in that: There are multiple initial solutions obtained in S21, and any result randomly generated by the strategy that satisfies the constraint condition is used as the initial solution.

7. The railway beam yard site selection method based on the VK combination algorithm according to claim 1 is characterized in that: The global evaluation function f′ in S5 is as follows: Among them, p′ k is the local optimal solution R n The coordinates of the center of the covered bridge, k is the bridge number, k∈[1,K], K is the total number of bridges.

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