Building material hoisting track self-adaptive optimization method, device, equipment and product

Abstract

The invention discloses a building material hoisting track self-adaptive optimization method, device, equipment and product, and relates to the technical field of intelligent control. Determining a plurality of material hoisting tasks on the basis of building material types and building material demanded quantities required by a plurality of material demand points of the building construction site; based on the multiple material hoisting tasks, the building material demand quantity constraints of the multiple material demand points, the building material supply type constraints of the multiple material supply points and the building material supply quantity constraints of the multiple material supply points, a particle population is initialized, and each particle in the particle population represents a building material hoisting scheme; establishing a target function by taking the hoisting time corresponding to the minimum building material hoisting scheme as a target; solving the particle population through a genetic algorithm to obtain an optimal particle individual; and determining final building material hoisting of the plurality of building material hoisting tasks based on the optimal particle individuals. The building material hoisting efficiency can be improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology, specifically relating to an adaptive optimization method, device, equipment, and product for building material hoisting trajectory. Background Technology

[0002] Tower cranes are the most important hoisting equipment on construction sites, enabling the convenient and quick hoisting of building materials.

[0003] During the hoisting of building materials (such as steel bars and pipes), cost considerations often necessitate the simultaneous hoisting of multiple material demand points within the coverage area using a single tower crane. However, traditional tower crane scheduling methods largely rely on the personal experience of hoisting personnel when controlling the hoisting schedule of different material demand points within the tower crane's coverage area, lacking a systematic consideration of the spatial location of material demand. This leads to unreasonable hoisting procedures during the building material hoisting process, resulting in irrational planning of tower crane transportation routes and repeated transportation, thus reducing the efficiency of building material hoisting.

[0004] Therefore, how to provide an effective solution to improve the efficiency of building material hoisting has become a pressing problem to be solved in the existing technology. Summary of the Invention

[0005] The purpose of this invention is to provide an adaptive optimization method, apparatus, equipment, and product for building material hoisting trajectory, in order to solve the above-mentioned problems existing in the prior art.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides an adaptive optimization method for the hoisting trajectory of building materials, comprising: Based on the types and quantities of building materials required at multiple material demand points on the construction site, multiple material hoisting tasks are identified. Based on the multiple material hoisting tasks, the building material demand constraints of multiple material demand points, the building material supply type constraints of multiple material supply points, and the building material supply quantity constraints of multiple material supply points, a particle population is initialized. Each particle in the particle population represents a building material hoisting scheme. The building material hoisting scheme includes the hoisting sequence of the multiple building material hoisting tasks and the material supply point corresponding to each building material hoisting task. An objective function is established with the goal of minimizing the hoisting time corresponding to the building material hoisting scheme. The hoisting time corresponding to the building material hoisting scheme is the sum of the hoisting time of each building material hoisting task in the building material hoisting scheme and the hoisting time of the empty transfer task between adjacent building material hoisting tasks. The optimal individual particle is obtained by solving the particle population using a genetic algorithm. Based on the optimal individual particles, the final building material hoisting scheme for the multiple building material hoisting tasks is determined, so that building materials can be hoisted to the multiple material demand points based on the hoisting trajectory corresponding to the final building material hoisting scheme.

[0007] In one possible design, the optimal individual particle is obtained by solving the particle population using a genetic algorithm, including: The objective function value of the building material hoisting scheme corresponding to each particle in the particle population is calculated based on the objective function. Based on the objective function value corresponding to each particle in the particle swarm, the fitness value corresponding to each particle in the particle swarm is determined. The fitness value corresponding to a particle is negatively correlated with the objective function value corresponding to the particle. Perform crossover and mutation operations on particles in the particle population to update the particle population; When the iteration stops, the particle with the highest fitness value in the latest particle population is selected as the optimal particle.

[0008] In one possible design, the objective function is: Where S represents the total number of material hoisting tasks, I represents the total number of material supply points, J represents the total number of material demand points, and M represents the total number of material types. This indicates that the tower crane hook will transport material m from material supply point i to material demand point j during the s-th material hoisting task. This represents the material transportation time from material supply point i to material demand point j. Indicates the time for loading building materials. Indicates the unloading time of building materials. This indicates that after the s-th material hoisting task, the tower crane hook will be transferred from the material demand point j to the next material supply point i+1. This indicates the lifting time for an empty hoisting transfer task that moves the hook from the material demand point j to the next material supply point i+1.

[0009] In one possible design, the material transport time for building materials from material supply point i to material demand point j is: ,in, This represents the horizontal travel time of the tower crane hook during the material hoisting task that transports building materials from material supply point i to material demand point j. β represents the vertical travel time of the tower crane hook during the material hoisting task of transporting building materials from material supply point i to material demand point j, and β represents the continuity between the horizontal and vertical movements of the tower crane hook.

[0010] In one possible design, the vertical travel time of the tower crane hook in the material hoisting task of transporting building materials from material supply point i to material demand point j is: ,in, This indicates the vertical speed of the tower crane hook. Indicates the height of material supply point i. represents the lifting height of the tower crane hook at the material demand point j, and h represents the height of the tower crane hook when unloading materials at the material demand point j; The horizontal travel time of the tower crane hook in the construction material hoisting task of transporting building materials from material supply point i to material demand point j ,in, This indicates the time it takes for the tower crane hook to move radially along the boom. The tangential motion time of the tower crane hook is represented by α, which represents the continuity between the radial and tangential motions of the tower crane hook.

[0011] In one possible design, crossover and mutation operations are performed on particles in the particle population to update the population, including: The particle population is updated by performing crossover and mutation operations on particles in the particle population using the roulette wheel algorithm.

[0012] In one possible design, the iteration stopping condition is that the number of iterations reaches a preset number of iterations.

[0013] Secondly, the present invention provides an adaptive optimization device for the hoisting trajectory of building materials, comprising: The first determining unit is used to determine multiple material hoisting tasks based on the types and quantities of building materials required at multiple material demand points on the construction site. An initialization unit is used to initialize a particle population based on the multiple material hoisting tasks, the building material demand constraints of multiple material demand points, the building material supply type constraints of multiple material supply points, and the building material supply quantity constraints of multiple material supply points. Each particle in the particle population represents a building material hoisting scheme, and the building material hoisting scheme includes the hoisting sequence of the multiple building material hoisting tasks and the material supply point corresponding to each building material hoisting task. The function establishment unit establishes an objective function with the goal of minimizing the hoisting time corresponding to the building material hoisting scheme. The hoisting time corresponding to the building material hoisting scheme is the sum of the hoisting time of each building material hoisting task in the building material hoisting scheme and the hoisting time of the empty transfer task between adjacent building material hoisting tasks. The solution unit is used to solve the particle population using a genetic algorithm to obtain the optimal individual particle. The second determining unit is used to determine the final building material hoisting scheme for the multiple building material hoisting tasks based on the optimal individual particles, so as to hoist building materials to the multiple material demand points based on the hoisting trajectory corresponding to the final building material hoisting scheme.

[0014] Thirdly, the present invention provides an adaptive optimization device for building material hoisting trajectory, comprising a memory, a processor, and a transceiver connected in sequence and communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the adaptive optimization method for building material hoisting trajectory as described in the first aspect or any possible design of the first aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, perform the adaptive optimization method for hoisting material trajectory as described in the first aspect or any possible design of the first aspect.

[0016] Fifthly, the present invention provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the adaptive optimization method for building material hoisting trajectory as described in the first aspect or any possible design of the first aspect.

[0017] Beneficial effects: This invention determines multiple material hoisting tasks based on the types and quantities of building materials required at multiple material demand points on a construction site. Based on these hoisting tasks, constraints on the quantity of building materials required at each material demand point, constraints on the type of building materials supplied at each material supply point, and constraints on the quantity of building materials supplied at each material supply point, a particle population is initialized. Each particle in the population represents a building material hoisting scheme, which includes the hoisting sequence of the multiple hoisting tasks and the corresponding material supply point. An objective function is established to minimize the hoisting time corresponding to each hoisting scheme, where the hoisting time is the sum of the hoisting time of each hoisting task within the scheme and the hoisting time of empty transfer tasks between adjacent hoisting tasks. A genetic algorithm is used to solve the particle population to obtain the optimal individual particle. Finally, based on the optimal individual particle, the final building material hoisting scheme for the multiple hoisting tasks is determined, enabling the hoisting of building materials to multiple material demand points based on the hoisting trajectory corresponding to the final hoisting scheme. In this way, the impact of the hoisting process can be fully considered during the hoisting of building materials. By optimizing the hoisting process, the total hoisting time can be shortened, thereby improving the efficiency of building material hoisting and facilitating practical application and promotion. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the adaptive optimization method for building material hoisting trajectory provided in this application embodiment; Figure 2 A block diagram illustrating the adaptive optimization device for building material hoisting trajectory provided in this application embodiment; Figure 3 This is a block diagram of the adaptive optimization device for building material hoisting trajectory provided in an embodiment of this application. Detailed Implementation

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0020] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0021] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0022] It should be understood that specific details are provided in the following description to facilitate a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, the system may be shown in block diagrams to avoid obscuring the example with unnecessary details. In other instances, well-known processes, structures, and techniques may be shown without unnecessary details to avoid obscuring the exemplary embodiments.

[0023] To improve the efficiency of building material hoisting, this application provides an adaptive optimization method, apparatus, equipment, and product for building material hoisting trajectory. This adaptive optimization method, apparatus, equipment, and product can optimize the hoisting process, shorten the total hoisting time, and improve the efficiency of building material hoisting.

[0024] like Figure 1 The diagram shown is a flowchart of an adaptive optimization method for building material hoisting trajectory provided in the first aspect of this application. This adaptive optimization method for building material hoisting trajectory may include, but is not limited to, the following steps S101-S105.

[0025] Step S101. Based on the types and quantities of building materials required at multiple material demand points on the construction site, determine multiple material hoisting tasks.

[0026] The material hoisting task records the corresponding material demand points, as well as the types and quantities of building materials required by those points.

[0027] For example, if a construction site includes material demand points A, B, C, and D, then four material hoisting tasks A1, B1, C1, and D1 can be generated. Each material hoisting task records the corresponding material demand point and parameters such as the type of building materials required by the material demand point and the required quantity of building materials. Assuming material demand point A requires 100 units of building material a, material demand point B requires 100 units of building material b, material demand point C requires 200 units of building material c, and material demand point D requires 100 units of building material a, then based on the types and quantities of building materials required by multiple material demand points at the construction site, in the four determined material hoisting tasks, material hoisting task A1 records material demand point A and the required building material type a and quantity 100; material hoisting task B1 records material demand point B and the required building material type b and quantity 100; material hoisting task C1 records material demand point C and the required building material type c and quantity 200; and material hoisting task D1 records material demand point D and the required building material type a and quantity 100.

[0028] Step S102. Initialize the particle population based on multiple material hoisting tasks, multiple material demand points' building material demand constraints, multiple material supply points' building material supply type constraints, and multiple material supply points' building material supply quantity constraints.

[0029] Each particle in the particle swarm represents a building material hoisting scheme, which includes the hoisting sequence of the multiple building material hoisting tasks and the material supply point corresponding to each building material hoisting task.

[0030] Specifically, when initializing the particle swarm, it is necessary to consider the building material demand at multiple material demand points, the building material supply types at multiple material supply points, and the building material supply quantities at multiple material supply points. Under the condition that the building material supply types and quantities at the material supply points meet the supply requirements, multiple building material hoisting schemes are generated. Each building material hoisting scheme includes the hoisting sequence of multiple building material hoisting tasks and the material supply points corresponding to each building material hoisting task.

[0031] Step S103. Establish an objective function with the goal of minimizing the hoisting time corresponding to the building material hoisting scheme.

[0032] The hoisting time corresponding to the building material hoisting scheme can be the sum of the hoisting time of each building material hoisting task in the scheme and the hoisting time of the empty hoisting transfer task between adjacent building material hoisting tasks. The empty hoisting transfer task between adjacent building material hoisting tasks refers to the task of transferring the tower crane hook to the material supply point corresponding to the next building material hoisting task after completing the previous building material hoisting task.

[0033] In one or more embodiments, the objective function can be expressed as: Where S represents the total number of material hoisting tasks, I represents the total number of material supply points, J represents the total number of material demand points, s represents the material hoisting task number, i represents the material supply point number, j represents the material demand point number, m represents the material number, and M represents the total number of material types. This indicates that the tower crane hook will transport material m from material supply point i to material demand point j during the s-th material hoisting task. This represents the material transportation time from material supply point i to material demand point j. Indicates the time for loading building materials. Indicates the unloading time of building materials. This indicates that after the s-th material hoisting task, the tower crane hook will be transferred from the material demand point j to the next material supply point i+1. This represents the lifting time for an empty hoisting task, transferring the hook from material demand point j to the next material supply point i+1. It should be noted that in the objective function, when i is 1, i+1 is 1.

[0034] The material transportation time for building materials from supply point i to demand point j can be expressed as follows: ,in, This represents the horizontal travel time of the tower crane hook during the material hoisting task that transports building materials from material supply point i to material demand point j. β represents the vertical travel time of the tower crane hook during the material hoisting task of transporting building materials from material supply point i to material demand point j. β represents the continuity between the horizontal and vertical movements of the tower crane hook, which is related to the operator's skill level. The higher the operator's skill level, the lower the value of β. The range of β can be set according to the actual situation. For example, the range of β can be [0, 1.2].

[0035] The vertical travel time of the tower crane hook in a construction material hoisting task that transports building materials from material supply point i to material demand point j can be expressed as: ,in, This indicates the vertical speed of the tower crane hook. Indicates the height of material supply point i. represents the lifting height of the tower crane hook at the material demand point j, and h represents the height of the tower crane hook when unloading materials at the material demand point j.

[0036] The horizontal travel time of the tower crane hook in a construction material hoisting task, which transports building materials from material supply point i to material demand point j, can be expressed as... ,in, This indicates the time it takes for the tower crane hook to move radially along the boom. The value of α represents the tangential motion time of the tower crane hook. α represents the continuity between the radial and tangential motions of the tower crane hook, which is related to the operator's skill level. The higher the operator's skill level, the lower the value of α. The range of α can be set according to the actual situation. For example, the range of α can be [0, 1.2].

[0037] The radial movement time of the tower crane hook along the boom and the tangential movement time of the tower crane hook can be calculated conventionally based on the location of the material demand point, the location of the material supply point, the position of the tower crane, the radial movement speed of the tower crane hook along the boom, and the tangential movement speed of the tower crane hook.

[0038] Step S104. Solve the particle population using a genetic algorithm to obtain the optimal individual particle.

[0039] In one or more embodiments, solving the particle population using a genetic algorithm may include, but is not limited to, the following steps S1041-S1044.

[0040] Step S1041. Calculate the objective function value of the building material hoisting scheme corresponding to each particle in the particle swarm based on the objective function.

[0041] Step S1042. Based on the objective function value corresponding to each particle in the particle swarm, determine the fitness value corresponding to each particle in the particle swarm.

[0042] The fitness value of a particle is negatively correlated with the objective function value. In one or more embodiments, the fitness value of a particle can be expressed as f = C / O. bj Where C is a constant, O bj This represents the objective function value corresponding to the particle.

[0043] Step S1043. Perform crossover and mutation operations on the particles in the particle population to update the particle population.

[0044] In one or more embodiments, the particle population can be updated by performing crossover and mutation operations on particles in the particle population using the roulette wheel algorithm.

[0045] Step S1044. When the iteration stopping condition is met, the particle with the largest corresponding fitness value in the latest particle population is taken as the optimal particle individual.

[0046] Specifically, iteration can be stopped when the number of iterations reaches the preset number of iterations or when there are particles in the particle population whose corresponding fitness value is greater than the preset fitness threshold.

[0047] Step S105. Based on the optimal individual particles, determine the final building material hoisting scheme for multiple building material hoisting tasks, so as to hoist building materials to multiple material demand points based on the hoisting trajectory corresponding to the final building material hoisting scheme.

[0048] The adaptive optimization method for building material hoisting trajectory provided by this invention determines multiple material hoisting tasks based on the types and quantities of building materials required at multiple material demand points on a construction site. Based on these hoisting tasks, constraints on the quantity of building materials required at the multiple material demand points, constraints on the type of building materials supplied at the multiple material supply points, and constraints on the quantity of building materials supplied at the multiple material supply points, a particle population is initialized, with each particle representing a building material hoisting scheme. An objective function is established to minimize the hoisting time corresponding to each hoisting scheme. Then, a genetic algorithm is used to solve the particle population to obtain the optimal individual particle. Finally, based on the optimal individual particle, the final building material hoisting scheme for the multiple hoisting tasks is determined, allowing building materials to be hoisted to the multiple material demand points based on the hoisting trajectory corresponding to the final hoisting scheme. In this way, the impact of hoisting procedures is fully considered during the building material hoisting process. By optimizing the hoisting procedures, the total hoisting time is shortened, thereby improving the efficiency of building material hoisting and facilitating practical application and promotion.

[0049] Please see Figure 2 The second aspect of this application provides a building material hoisting trajectory adaptive optimization device, which includes: The first determining unit is used to determine multiple material hoisting tasks based on the types and quantities of building materials required at multiple material demand points on the construction site. An initialization unit is used to initialize a particle population based on the multiple material hoisting tasks, the building material demand constraints of multiple material demand points, the building material supply type constraints of multiple material supply points, and the building material supply quantity constraints of multiple material supply points. Each particle in the particle population represents a building material hoisting scheme, and the building material hoisting scheme includes the hoisting sequence of the multiple building material hoisting tasks and the material supply point corresponding to each building material hoisting task. The function establishment unit establishes an objective function with the goal of minimizing the hoisting time corresponding to the building material hoisting scheme. The hoisting time corresponding to the building material hoisting scheme is the sum of the hoisting time of each building material hoisting task in the building material hoisting scheme and the hoisting time of the empty transfer task between adjacent building material hoisting tasks. The solution unit is used to solve the particle population using a genetic algorithm to obtain the optimal individual particle. The second determining unit is used to determine the final building material hoisting scheme for the multiple building material hoisting tasks based on the optimal individual particles, so as to hoist building materials to the multiple material demand points based on the hoisting trajectory corresponding to the final building material hoisting scheme.

[0050] The working process, working details and technical effects of the adaptive optimization device for building material hoisting trajectory provided in the second aspect of this embodiment can be found in the first aspect of the embodiment, and will not be repeated here.

[0051] Please see Figure 3 The third aspect of this application provides a building material hoisting trajectory adaptive optimization device, including a memory, a processor, and a transceiver that are sequentially and communicatively connected. The memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the building material hoisting trajectory adaptive optimization method as described in the first aspect of the application.

[0052] Specifically, the memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out (FIFO) memory, and / or last-in-first-out (FILO) memory, etc.; the processor may not be limited to microprocessors of the STM32F105 series, ARM (Advanced RISC Machines), x86 architecture processors, or processors with integrated NPU (neural-network processing units); the transceiver may be, but is not limited to, WiFi (Wireless Fidelity) wireless transceivers, Bluetooth wireless transceivers, General Packet Radio Service (GPRS) wireless transceivers, ZigBee (a low-power LAN protocol based on the IEEE 802.15.4 standard), 3G transceivers, 4G transceivers, and / or 5G transceivers, etc.

[0053] This fourth aspect of the embodiment provides a computer-readable storage medium storing instructions containing the adaptive optimization method for building material hoisting trajectory as described in the first aspect of the embodiment. Specifically, the computer-readable storage medium stores instructions that, when executed on a computer, perform the adaptive optimization method for building material hoisting trajectory as described in the first aspect. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or memory sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0054] The fifth aspect of this embodiment provides a computer program product containing instructions that, when executed on a computer, cause the computer to perform the adaptive optimization method for building material hoisting trajectory as described in the first aspect of this embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0055] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for building material hoisting trajectory adaptive optimization, characterized in that, The method comprises the following steps: determining a plurality of material hoisting tasks based on the types and quantities of construction materials required by a plurality of material demand points in a construction site; initializing a particle population based on the plurality of material hoisting tasks, the quantity constraints of construction materials of the plurality of material demand points, the type constraints of construction materials of the plurality of material supply points, and the quantity constraints of construction materials of the plurality of material supply points, wherein each particle in the particle population represents a construction material hoisting scheme, and the construction material hoisting scheme comprises the hoisting sequence of the plurality of construction material hoisting tasks and the material supply points corresponding to each construction material hoisting task; establishing an objective function aiming at minimizing the hoisting time corresponding to the construction material hoisting scheme, wherein the hoisting time corresponding to the construction material hoisting scheme is the sum of the hoisting time of each construction material hoisting task and the hoisting time of the empty hoisting transfer task between adjacent construction material hoisting tasks in the construction material hoisting scheme; solving the particle population by a genetic algorithm to obtain an optimal particle individual; determining a final construction material hoisting scheme of the plurality of construction material hoisting tasks based on the optimal particle individual, so as to hoist construction materials to the plurality of material demand points based on the hoisting track corresponding to the final construction material hoisting scheme.

2. The building material hoist trajectory self-adaptive optimization method according to claim 1, characterized in that, The solving of the particle population by the genetic algorithm to obtain the optimal particle individual comprises the following steps: calculating the objective function value of the construction material hoisting scheme corresponding to each particle in the particle population based on the objective function; determining the fitness value of each particle in the particle population corresponding to the objective function value, wherein the fitness value of the particle is negatively correlated with the objective function value of the particle; updating the particle population by performing cross and mutation operations on the particles in the particle population; when the iteration stopping condition is reached, taking the particle with the maximum corresponding fitness value in the latest particle population as the optimal particle individual.

3. The building material hoist trajectory self-adaptive optimization method according to claim 2, characterized in that, The objective function is wherein S represents the total number of material hoisting tasks, I represents the total number of material supply points, J represents the total number of material demand points, and M represents the total number of material types, represents the transportation of material m from material supply point i to material demand point j by the tower crane hook under the s th building material hoisting task, represents the material transportation time of transporting building material from material supply point i to material demand point j, represents the building material loading time, represents the building material unloading time, represents the empty hoisting transfer of the tower crane hook from material demand point j to the next material supply point i+1 after the s th building material hoisting task, represents the hoisting time of the empty hoisting transfer task of transferring the hook from material demand point j to the next material supply point i+1.

4. The method of claim 3, wherein, The material transport time of the building material from the material supply point i to the material demand point j is wherein denotes the horizontal movement time of the tower crane hook in the building material hoisting task for transporting the building material from the material supply point i to the material demand point j, denotes the vertical movement time of the tower crane hook in the building material hoisting task for transporting the building material from the material supply point i to the material demand point j, and β denotes the continuity of the horizontal movement and the vertical movement of the tower crane hook.

5. The method of claim 4, wherein, The vertical run time of the tower crane hook in the construction material hoisting task transporting construction material from the material supply point i to the material demand point j is wherein denotes the vertical movement speed of the tower crane hook, denotes the height of the material supply point i, denotes the hoisting height of the tower crane hook at the material demand point j, h denotes the height of the tower crane hook when unloading the material at the material demand point j; The horizontal movement time of the tower crane hook in the construction material hoisting task of transporting construction material from a material supply point i to a material demand point j is wherein denotes the radial movement time of the tower crane hook along the boom, denotes the tangential movement time of the tower crane hook, and α denotes the coherence of the radial movement and the tangential movement of the tower crane hook.

6. The method of claim 2, wherein, The updating of the particle population by performing cross and mutation operations on the particles in the particle population comprises the following steps: updating the particle population by performing cross and mutation operations on the particles in the particle population by a roulette algorithm.

7. The method of claim 2, wherein, The iteration stopping condition is that the number of iterations reaches a preset number of iterations.

8. A building material hoisting trajectory self-adaptive optimization device, characterized in that, The method comprises the following steps: a first determination unit is configured to determine a plurality of material hoisting tasks based on the types and quantities of construction materials required by a plurality of material demand points in a construction site; an initialization unit is configured to initialize a particle population based on the plurality of material hoisting tasks, the quantity constraints of construction materials of the plurality of material demand points, the type constraints of construction materials of the plurality of material supply points, and the quantity constraints of construction materials of the plurality of material supply points, wherein each particle in the particle population represents a construction material hoisting scheme, and the construction material hoisting scheme comprises the hoisting sequence of the plurality of construction material hoisting tasks and the material supply points corresponding to each construction material hoisting task; The function establishing unit establishes a target function with the aim of minimizing the hoisting time corresponding to the building material hoisting scheme, wherein the hoisting time corresponding to the building material hoisting scheme is the sum of the hoisting time of each building material hoisting task in the building material hoisting scheme and the hoisting time of the empty hoisting transfer task between adjacent building material hoisting tasks; The solving unit is configured to solve the particle population by using a genetic algorithm to obtain an optimal particle individual; The second determining unit is configured to determine a final building material hoisting scheme of the plurality of building material hoisting tasks based on the optimal particle individual, so as to hoist the building material to the plurality of material demand points based on the hoisting track corresponding to the final building material hoisting scheme.

9. A building material hoisting trajectory self-adaptive optimization device, characterized in that, The computer program or the instructions realize the building material hoisting track adaptive optimization method as claimed in any one of claims 1-7 when executed by a computer.

10. A computer program product comprising computer programs or instructions, characterized in that, ​

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