Multi-dimensional engineering cost analysis and comparison method

Abstract

The invention provides a multi-dimensional engineering cost analysis and comparison method, which comprises the following steps of: obtaining an engineering construction plan, and constructing a time sequence according to construction time nodes in the engineering construction plan; acquiring spatial data and resource data according to the engineering construction plan; randomly mapping the spatial data and the resource data to a time period formed by construction time nodes in a time sequence according to different time nodes to obtain a construction sequence; calculating the viscosity of adjacent time periods in the construction sequence, and adding the viscosity into the construction sequence; a sparrow search algorithm is adopted to analyze and compare the construction sequence based on the lowest cost, and an optimal construction sequence is obtained; a time dimension, a space dimension and a resource dimension are combined together to construct a time sequence, and after the viscosity between a logistics supplier and a resource provider is considered, a sparrow search algorithm is adopted for optimization, so that an optimal construction sequence with the lowest construction cost evaluated from multiple dimensions can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering design, and in particular to a multi-dimensional engineering cost analysis and comparison method. Background Art

[0002] In engineering project management, cost analysis is a crucial link. Engineering cost refers to the costs of labor, materials, engineering equipment, construction machinery shifts and their management that must be consumed or used throughout the entire process from the beginning to the end of the construction, as well as the fees and taxes paid in accordance with regulations. With the continuous expansion of the scale and complexity of engineering projects, the factors affecting engineering costs are becoming increasingly diverse. In addition to direct material, labor and equipment costs, they are also affected by changes in different construction stages, cost differences in different geographical locations, changes in consumption of different resource types, etc., and these influences do not directly affect cost changes. However, when evaluating engineering costs, people often focus on data comparison in a single dimension, such as direct costs, indirect costs or total costs. Although this method is simple and intuitive, it is difficult to fully reflect the complexity and diversity of engineering costs and cannot correctly evaluate engineering costs. In addition, when evaluating engineering costs, reasonable construction units will be selected based on different engineering teams, construction parties, etc. Due to the long construction period, the types of construction parties selected in different construction stages will be different. When comparing and costing, the amount of data is large, and it is impossible to quickly and accurately analyze the costs of different construction unit combinations for comparison. Summary of the invention

[0003] In view of this, the present invention proposes a multi-dimensional engineering cost analysis and comparison method, which can analyze and compare engineering costs from different dimensions and obtain the optimal construction sequence to minimize the construction cost.

[0004] The technical solution of the present invention is achieved in this way:

[0005] A multi-dimensional engineering cost analysis and comparison method comprises the following steps:

[0006] Step S1, obtaining a construction plan, and constructing a time series according to the construction time nodes in the construction plan;

[0007] Step S2: Acquire spatial data and resource data according to the engineering construction plan;

[0008] Step S3, randomly mapping the spatial data and resource data to the time periods composed of the construction time nodes in the time sequence according to different time nodes, to obtain a construction sequence;

[0009] Step S4, calculating the viscosity of adjacent time periods in the construction sequence, and adding the viscosity to the construction sequence;

[0010] Step S5: Use the sparrow search algorithm to analyze and compare the construction sequences based on the lowest cost, and obtain the optimal construction sequence.

[0011] Preferably, the specific steps of step S1 include:

[0012] Step S11, obtaining a construction plan, and extracting a start time node and an end time node in the construction plan;

[0013] Step S12: construct a time series according to the start time node and the end time node;

[0014] Step S13: Obtain the construction time period of each construction task from the engineering construction plan, and insert the construction time period into the time series.

[0015] Preferably, the specific steps of obtaining spatial data according to the engineering construction plan in step S2 include:

[0016] Step S21, obtaining the specific construction location according to the engineering construction plan;

[0017] Step S22, query the logistics supplier of the specific construction location, and obtain the cost of transportation from the logistics supplier to the specific construction location;

[0018] Step S23: Obtain the average labor market cost of the specific construction location.

[0019] Preferably, the specific steps of obtaining resource data according to the engineering construction plan in step S2 include:

[0020] Step S24: Obtain the human resources, material resources, equipment resources, and energy resources required for each construction stage according to the project construction plan;

[0021] Step S25, querying resource providers based on human resources, material resources, equipment resources, and energy resources;

[0022] Step S26: Obtain quotation data from resource providers.

[0023] Preferably, the specific steps of step S3 include:

[0024] Step S31, dividing the time series into several time periods according to the construction time nodes;

[0025] Step S32: According to the construction requirements in each time period, randomly select corresponding logistics suppliers, labor market average levels, and resource providers to map to the time period;

[0026] Step S33: regroup the time periods into several construction sequences according to the time sequence.

[0027] Preferably, the specific steps of step S4 include:

[0028] Step S41: Select a logistics supplier or resource provider in a certain time period and record it as a preceding unit;

[0029] Step S42, calculating the first correlation degree and the second correlation degree between the preceding unit and the logistics supplier and the resource provider in the following time period;

[0030] Step S43: Add the first correlation degree and the second correlation degree to obtain viscosity, and add the viscosity between the corresponding two time periods.

[0031] Preferably, the specific steps of step S42 are: querying the historical cooperation times and key performance indicators between the preceding unit and the logistics suppliers and resource providers in the succeeding time period, assigning values ​​to the historical cooperation times and key performance indicators respectively and then summing them, and outputting the summation results as the first correlation degree and the second correlation degree.

[0032] Preferably, the specific steps of step S5 include:

[0033] Step S51, initializing the sparrow population and setting the number of iterations;

[0034] Step S52: randomly select a construction sequence, and calculate the fitness value of the sparrow based on the lowest cost;

[0035] Step S53, selecting another construction sequence, calculating the fitness value, comparing it with the fitness value calculated last time, and retaining the construction sequence with the largest fitness value;

[0036] Step S54: perform iterative calculation to obtain the construction sequence with the maximum fitness value, and output it as the optimal construction sequence.

[0037] Preferably, the number of iterations is the number of construction sequences.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] ① According to the construction plan, time series, spatial data and resource data can be obtained. The spatial data and resource data are processed separately and mapped to the time series to obtain the construction sequence. When calculating the cost, it does not only consider a single dimension, but combines multiple dimensions of time, space and resources, which can improve the accuracy of cost calculation, so as to reasonably evaluate and select the corresponding construction unit;

[0040] ② After determining the construction sequence, the viscosity of the construction units in adjacent time periods in the construction sequence will also be taken into account. After forming a new construction sequence, the sparrow search algorithm is used to find the optimal construction sequence. When the construction units are selected based on the optimal construction sequence, the cost of engineering construction can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A flowchart of a multi-dimensional engineering cost analysis and comparison method of the present invention;

[0043] Figure 2 A flowchart of step S1 of a multi-dimensional engineering cost analysis and comparison method of the present invention;

[0044] Figure 3 A flowchart of step S2 of a multi-dimensional engineering cost analysis and comparison method of the present invention;

[0045] Figure 4 It is a flowchart of step S3 of a multi-dimensional engineering cost analysis and comparison method of the present invention;

[0046] Figure 5 It is a flowchart of step S4 of a multi-dimensional engineering cost analysis and comparison method of the present invention;

[0047] Figure 6 It is a flowchart of step S5 of a multi-dimensional engineering cost analysis and comparison method of the present invention; DETAILED DESCRIPTION

[0048] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0049] See also Figures 1 to 6 The present invention provides a multi-dimensional engineering cost analysis and comparison method, comprising the following steps:

[0050] Step S1, obtaining a construction plan, and constructing a time series according to the construction time nodes in the construction plan;

[0051] Step S2: Acquire spatial data and resource data according to the engineering construction plan;

[0052] Step S3, randomly mapping the spatial data and resource data to the time periods composed of the construction time nodes in the time sequence according to different time nodes, to obtain a construction sequence;

[0053] Step S4, calculating the viscosity of adjacent time periods in the construction sequence, and adding the viscosity to the construction sequence;

[0054] Step S5: Use the sparrow search algorithm to analyze and compare the construction sequences based on the lowest cost, and obtain the optimal construction sequence.

[0055] A multi-dimensional engineering cost analysis and comparison method of the present invention analyzes, calculates and compares the overall cost of engineering construction. When performing the analysis, the engineering construction plan is obtained, and each construction time node is found from the engineering construction plan. Each construction node represents a change in the engineering construction. For example, the start node is the start time of the engineering construction, and the design node is the node where the engineering construction starts to design drawings. After obtaining the construction time nodes in the entire engineering construction plan, a time series based on the entire construction plan can be constructed. This time series includes the start and end of the construction and each construction stage. There are differences in the types of work in each construction stage, and there are also differences in specific construction tasks. Therefore, from the engineering construction plan, Specific construction tasks can be obtained from the construction plan, and then the spatial data and resource data required for construction can be obtained according to different construction tasks. Then, the corresponding spatial data and resource data required for each construction stage are mapped to the time period of the time series to form a complete construction sequence. The selected spatial data and resource data are not single. Different combinations of spatial data and resource data can form multiple construction sequences. Finally, the optimal construction sequence can be obtained by optimizing the construction sequence. Since the spatial dimension and resource dimension are combined with the time dimension, multi-dimensional content can be comprehensively compared for cost analysis. The evaluated project cost can more accurately reflect the actual situation of the project construction.

[0056] After obtaining several construction sequences, the construction sequences need to be further processed. The construction sequence will be divided into several time periods. The types of construction in each time period are different, and the corresponding construction units will also be different. The viscosity between construction units between adjacent time periods determines the smooth handover of work and whether subsequent work can be carried out quickly. Therefore, in each construction sequence, the viscosity of adjacent time periods will be calculated and added to the construction sequence. After being used as the basis for optimizing the construction sequence, the sparrow optimization algorithm is used to optimize the construction sequence. The optimal construction sequence obtained is the optimal construction sequence that reflects the evaluation from multiple dimensions and considers the viscosity of the construction units. When the construction units are selected according to the optimal construction sequence for construction, the cost is the lowest.

[0057] Preferably, the specific steps of step S1 include:

[0058] Step S11, obtaining a construction plan, and extracting a start time node and an end time node in the construction plan;

[0059] Step S12: construct a time series according to the start time node and the end time node;

[0060] Step S13: Obtain the construction time period of each construction task from the engineering construction plan, and insert the construction time period into the time series.

[0061] The construction plan includes the beginning and end of the entire construction process, that is, it includes the starting time node and the ending time node. The complete time series can be directly constructed based on the starting time node and the ending time node. The construction plan will also specify each construction task, such as preliminary investigation tasks, design tasks, construction tasks, etc. Different construction tasks will have specific and complete construction time periods. Therefore, after the construction time period is inserted into the time series, a time series containing each construction task in the entire construction process can be formed.

[0062] Preferably, the specific steps of obtaining spatial data according to the engineering construction plan in step S2 include:

[0063] Step S21, obtaining the specific construction location according to the engineering construction plan;

[0064] Step S22, query the logistics supplier of the specific construction location, and obtain the cost of transportation from the logistics supplier to the specific construction location;

[0065] Step S23, obtaining the average labor market cost of the specific construction location;

[0066] Step S24: Obtain the human resources, material resources, equipment resources, and energy resources required for each construction stage according to the project construction plan;

[0067] Step S25, querying resource providers based on human resources, material resources, equipment resources, and energy resources;

[0068] Step S26: Obtain quotation data from resource providers.

[0069] After obtaining the time series, it is necessary to determine how to carry out construction in each construction period, including the logistics required for construction and the corresponding resources. As for logistics, local logistics companies are generally selected to minimize costs. Therefore, the specific location of the construction project can be obtained through the construction plan. According to the specific location of the construction, all logistics suppliers in the corresponding area can be obtained. The transportation cost can be calculated based on the actual location of the logistics supplier, logistics route, transportation quotation, etc. At the same time, for the specific location of the construction, the corresponding average labor market cost can be queried. The average labor market cost and logistics suppliers can constitute the spatial dimension data.

[0070] In the engineering construction plan, according to the different types of construction, you can also query the required human resources, material resources, equipment resources and energy resources. Human resources include the number of skilled workers in different trades, their skill levels and work efficiency, while material resources include the quantity and quality of building materials, waterproof and thermal insulation materials, etc. Equipment resources include the required types of construction machinery, the rental or purchase cost of equipment, and energy resources include the usage of energy such as electricity, water and gas. Different resources correspond to different resource providers. According to the energy resources, you can query several resource providers, and then obtain the quotation data of the resource providers.

[0071] Preferably, the specific steps of step S3 include:

[0072] Step S31, dividing the time series into several time periods according to the construction time nodes;

[0073] Step S32: According to the construction requirements in each time period, randomly select corresponding logistics suppliers, labor market average levels, and resource providers to map to the time period;

[0074] Step S33: regroup the time periods into several construction sequences according to the time sequence.

[0075] After obtaining the spatial data and resource data, they need to be mapped to a time series. For a time series, it is divided into several time periods. Each time period corresponds to a different construction task. Different construction tasks select different logistics suppliers and resource providers. There may be multiple logistics suppliers and resource providers corresponding to the same construction task. Therefore, when performing random mapping, several construction sequences can be obtained according to different combinations. Each construction sequence contains several logistics suppliers and resource providers. Any construction sequence can complete the construction project, but the cost required for the construction project will vary greatly.

[0076] Preferably, the specific steps of step S4 include:

[0077] Step S41: Select a logistics supplier or resource provider in a certain time period and record it as a preceding unit;

[0078] Step S42, calculating the first correlation degree and the second correlation degree between the preceding unit and the logistics supplier and the resource provider in the following time period, specifically, querying the historical cooperation times and key performance indicators between the preceding unit and the logistics supplier and the resource provider in the following time period, assigning values ​​to the historical cooperation times and the key performance indicators respectively and then summing them, and outputting the summation results as the first correlation degree and the second correlation degree;

[0079] Step S43: Add the first correlation degree and the second correlation degree to obtain viscosity, and add the viscosity between the corresponding two time periods.

[0080] After obtaining the construction sequence, it is also necessary to consider the viscosity between the logistics suppliers and resource providers in the previous and next time periods. After selecting the logistics suppliers or resource providers in the previous time period, they can be recorded as the previous unit. There is a certain correlation between the previous unit and the logistics suppliers and resource providers in the next time period. The first correlation and the second correlation can be obtained by calculation. When calculating the correlation, it is necessary to consider the historical cooperation times and key performance indicators of the logistics suppliers and resource providers in the previous unit and the next time period. The more historical cooperation times, the higher the trust between the two companies, and the more tacit cooperation and running-in degree between them, which is more beneficial for the subsequent handover and construction transfer. In addition, the key performance indicators include on-time delivery rate, quality pass rate, and response time. A relatively high key performance indicator represents a higher degree of completion of the company. After assigning values ​​to the historical cooperation times and key performance indicators respectively, the data can be unified and summed to obtain the first correlation and the second correlation. Finally, the viscosity between the companies in adjacent time periods can be obtained by adding the first correlation and the second correlation. The viscosity is added between the corresponding two time periods to form a construction sequence.

[0081] Preferably, the specific steps of step S5 include:

[0082] Step S51, initialize the sparrow population and set the number of iterations, which is the number of construction sequences;

[0083] Step S52: randomly select a construction sequence, and calculate the fitness value of the sparrow based on the lowest cost;

[0084] Step S53, selecting another construction sequence, calculating the fitness value, comparing it with the fitness value calculated last time, and retaining the construction sequence with the largest fitness value;

[0085] Step S54: perform iterative calculation to obtain the construction sequence with the maximum fitness value, and output it as the optimal construction sequence.

[0086] After obtaining several construction sequences, the present invention adopts the sparrow search algorithm to optimize the construction sequence. After calculating the fitness values ​​of all construction sequences, the fitness values ​​are compared and analyzed, and the construction sequence with the largest fitness value is retained. Then, the optimal construction sequence can be obtained, and the cost of the optimal construction sequence is the lowest. When construction is performed based on the optimal construction sequence, the construction cost is the lowest.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-dimensional engineering cost analysis and comparison method, characterized in that: The following steps are involved: Step S1, obtaining a construction plan, and constructing a time series according to the construction time nodes in the construction plan; Step S2: Acquire spatial data and resource data according to the engineering construction plan; Step S3, randomly mapping the spatial data and resource data to the time periods composed of the construction time nodes in the time sequence according to different time nodes, to obtain a construction sequence; Step S4, calculating the viscosity of adjacent time periods in the construction sequence, and adding the viscosity to the construction sequence; Step S5: Use the sparrow search algorithm to analyze and compare the construction sequences based on the lowest cost, and obtain the optimal construction sequence.

2. A multi-dimensional engineering cost analysis and comparison method according to claim 1, characterized in that: The specific steps of step S1 include: Step S11, obtaining a construction plan, and extracting a start time node and an end time node in the construction plan; Step S12: construct a time series according to the start time node and the end time node; Step S13: Obtain the construction time period of each construction task from the engineering construction plan, and insert the construction time period into the time series.

3. A multi-dimensional engineering cost analysis and comparison method according to claim 1, characterized in that: The specific steps of step S2 for obtaining spatial data according to the engineering construction plan include: Step S21, obtaining the specific construction location according to the engineering construction plan; Step S22, query the logistics supplier of the specific construction location, and obtain the cost of transportation from the logistics supplier to the specific construction location; Step S23: Obtain the average labor market cost of the specific construction location.

4. A multi-dimensional engineering cost analysis and comparison method according to claim 3, characterized in that: The specific steps of step S2 for obtaining resource data according to the engineering construction plan include: Step S24: Obtain the human resources, material resources, equipment resources, and energy resources required for each construction stage according to the project construction plan; Step S25, querying resource providers based on human resources, material resources, equipment resources, and energy resources; Step S26: Obtain quotation data from resource providers.

5. A multi-dimensional engineering cost analysis and comparison method according to claim 4, characterized in that: The specific steps of step S3 include: Step S31, dividing the time series into several time periods according to the construction time nodes; Step S32: According to the construction requirements in each time period, randomly select corresponding logistics suppliers, labor market average levels, and resource providers to map to the time period; Step S33: regroup the time periods into several construction sequences according to the time sequence.

6. A multi-dimensional engineering cost analysis and comparison method according to claim 4, characterized in that: The specific steps of step S4 include: Step S41: Select a logistics supplier or resource provider in a certain time period and record it as a preceding unit; Step S42, calculating the first correlation degree and the second correlation degree between the preceding unit and the logistics supplier and the resource provider in the following time period; Step S43: Add the first correlation degree and the second correlation degree to obtain viscosity, and add the viscosity between the two corresponding time periods.

7. A multi-dimensional engineering cost analysis and comparison method according to claim 6, characterized in that: The specific steps of step S42 are: querying the historical cooperation times and key performance indicators between the previous unit and the logistics suppliers and resource providers in the next time period, assigning values ​​to the historical cooperation times and key performance indicators respectively and then summing them, and outputting the summation results as the first correlation degree and the second correlation degree.

8. A multi-dimensional engineering cost analysis and comparison method according to claim 1, characterized in that: The specific steps of step S5 include: Step S51, initializing the sparrow population and setting the number of iterations; Step S52: randomly select a construction sequence, and calculate the fitness value of the sparrow based on the lowest cost; Step S53, selecting another construction sequence, calculating the fitness value, comparing it with the fitness value calculated last time, and retaining the construction sequence with the largest fitness value; Step S54: perform iterative calculation to obtain the construction sequence with the maximum fitness value, and output it as the optimal construction sequence.

9. A multi-dimensional engineering cost analysis and comparison method according to claim 8, characterized in that: The number of iterations is the number of construction sequences.

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